17 jobs found

Senior Data Analyst BI & Data London Intermediate Full-time Description Minute Media is a global technology and content company built for the future of sports consumption. Minute Media's proprietary technology platform enables the creation, distribution, and monetization of digital content experiences, powering Minute Media's portfolio of trusted content brands, including Sports Illustrated, The Players' Tribune, and FanSided, as well as third-party publishers and advertisers. The technology platform also includes STN Video, an online video platform (OVP) that provides access to a robust sports highlights rights portfolio. Minute Media is building the future of how the world connects with sport, powered by innovation, shared globally, and trusted by millions of fans and the partners we serve. For more information, visit . We are looking for a data-driven Data Analyst specializing in LTV (Lifetime Value) & Subscriptions to join our London team. You will support all analytics related to our subscription products and user lifecycle. In this role, you will dive deep into subscriber behavior and churn patterns, develop models to project customer lifetime value, and help drive strategies to improve retention. You'll work closely with our Growth, Product, and Editorial teams to ensure data-driven decision-making in areas like paywall optimization, subscriber engagement, and content strategy for member audiences. This is a mid-level, full-time, hybrid on-site role ideal for someone passionate about using data to fuel audience growth and loyalty. What You'll Do Subscription Funnel & User Insights Analyze the subscription funnel end to end, tracking users from anonymous visitors to registered users and paying subscribers in order to identify drop-off points, conversion bottlenecks, and opportunities to improve sign-up rates. Monitor key subscription and user engagement metrics through daily, weekly, and monthly dashboards, and own analysis of metric changes over time. Perform deep-dive analyses on user retention. Present user insights to stakeholders by clearly identifying our most valuable users and what drives their engagement, and go beyond reporting by recommending concrete next steps to inform content and marketing decisions. LTV & Churn Modeling Develop and maintain subscriber Lifetime Value (LTV) models, continuously refining them by incorporating new data to improve accuracy. Build and improve churn prediction models to proactively identify at risk subscribers, using statistical or machine learning techniques as needed. Work with large subscription and engagement datasets to calculate LTV and churn while accounting for promotional pricing, seasonality, and content engagement. Translate model outputs into clear, actionable business recommendations. Cross-Functional Collaboration Collaborate with Growth and Marketing teams to define success measurement plans for initiatives. Work closely with Product Managers and Engineers to ensure user interaction data is accurately captured and available in the data warehouse, and advocate for new data collection where it would improve LTV or churn analysis. Partner with data and product teams to uncover trends in subscription behavior, including content engagement and the impact of new features on loyalty. Communicate insights and recommendations clearly to both technical and non-technical audiences, tailoring depth and format to drive understanding and action. Requirements What You Have You have 5+ years of experience in data analysis or data science, with a focus on user lifecycle, customer analytics, or subscription metrics. You bring advanced SQL skills and are comfortable querying and manipulating large datasets in a cloud data warehouse environment. You have experience building and maintaining data pipelines or intermediate data models, transforming raw event logs into aggregated, analysis-ready datasets for high-performance reporting. You have worked with BI and data visualization tools, ideally Looker Studio, to build dashboards and reports that track KPIs over time. You are familiar with statistical analysis and predictive modeling concepts such as cohort analysis, regression, survival analysis, experimentation, and churn prediction, even if you are not a dedicated data scientist. You demonstrate strong problem-solving skills and attention to detail, with the ability to validate data integrity, spot anomalies, and ensure accurate calculation of metrics like LTV. You understand experimental design in product or marketing contexts, including defining success metrics, determining sample sizes, and evaluating statistical significance. You communicate complex analytical findings clearly and make data-driven recommendations. You work effectively across functions and manage multiple priorities in a dynamic environment. You hold a B.Sc./B.A. in Statistics, Economics, Business, Computer Science, or a related field, or equivalent practical experience. Advantageous Previous experience in subscription-based digital media or a similar industry (e.g., streaming services, membership products) where you've worked on subscriber analytics. Hands on experience with subscription management or CRM platforms (such as Piano, Zuora, Stripe, or Salesforce Marketing Cloud) - understanding their data structures and how to extract meaningful insights from them. Knowledge of customer segmentation and personalization strategies, possibly using CDP (Customer Data Platform) tools like BlueConic. Programming skills in Python or R for advanced data analysis or to implement custom predictive models beyond basic SQL (e.g., using libraries for churn modeling or LTV projections). Experience analyzing web/app user behavior using tools like Google Analytics or Mixpanel, especially if related to funnel analysis or retention tracking. A passion for sports and familiarity with Minute Media's content - understanding our audience's interests can help in crafting more relevant insights. What You'll Get Opportunity to make a meaningful impact in a fast-growing company. Career development opportunities & different skill-based workshops offered each quarter. Central London based office. Hybrid work model. Cycle to Work scheme. Hybrid vacation model. Extended parental leave. Private Health Insurance including mental health, dental and optical cover. Standard access to WellHub with options to upgrade to premium membership. Fun company events and celebrations with a focus on DEI each quarter. Community involvement opportunities, both in-person and remote. Minute Media is committed to creating a diverse and inclusive work environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Overview Ekimetrics is a global leader in Marketing Effectiveness and AI-powered solutions. Since 2006, we have helped businesses optimise marketing and operations by combining AI with business and tech expertise across four domains: Marketing Effectiveness, Customer Analytics, Operational Excellence, ESG & sustainability. With in-house teams and offices in Paris, London, New York, Hong Kong, and Shanghai, we deliver tailor-made solutions that turn data into real positive impact, leveraging our technology and services. Our mission is to harness AI at scale with responsibility and values-driven work. Your responsibilities As a Senior Analyst specialising in Data Science & Marketing Effectiveness, you will lead the delivery of high-impact MMM programmes for international clients across industries such as Auto, Beauty, Retail, and Financial Services. You will manage small teams, oversee end-to-end project delivery, and ensure actionable insights are delivered to clients. Lead Projects Lead end-to-end MMM and marketing effectiveness programs for international clients, from data strategy and collection to modelling, insights, and activation. Apply econometrics, regression, Bayesian statistics, and machine learning methods to analyse marketing and customer data. Collaborate closely with Managers to understand the project scope, structure, analytical approaches, manage operations and ensure timely delivery. Build dashboards and visualisation tools to communicate actionable insights using proprietary Ekimetrics frameworks and best practices. Translate complex analytics into clear, business-oriented recommendations for senior stakeholders and C-suite clients. Support clients in optimising marketing spend, understanding campaign performance, improving customer segmentation, and maximising ROI. Client & Account Management Serve as the day-to-day operational contact for clients, building trustful relationships and proactively identifying growth opportunities. Present findings, recommendations, and actionable insights in client-facing workshops and executive presentations. Collaborate closely with managers and partners to develop proposals for new or expanded work, aligned with Ekimetrics' commercial offerings. People & Project Leadership Lead teams of 3-10 colleagues across multiple projects, ensuring high-quality delivery, client satisfaction, and profitability. Mentor and develop junior team members, strengthening technical, analytical, and client-facing competencies. Share best practices and contribute to internal knowledge management initiatives. Practice & Business Growth Identify opportunities for account growth and contribute to development with existing and prospective clients. Act as an ambassador of Eki culture by supporting transversal initiatives (e.g., Thought Leadership, Knowledge Management, Recruitment and Innovation). Champion and role-model our core values: Curiosity, Creativity, Excellence, Transmission, Pleasure. Your profile Experience & Technical Skills Strong 3-4 years' experience in marketing effectiveness/MMM and analytics/data science. Bachelor's or master's degree in Statistics, Econometrics, Data Science, Economics, Applied Mathematics, Marketing Analytics, or related field. Strong proficiency in Python, R, SQL, or similar tools. Experience with Databricks, Azure, or other cloud/data platforms is a plus. Solid understanding of econometrics, regression analysis, Bayesian statistics, or other advanced modelling techniques. Experience translating data and model outputs into actionable business recommendations. Comfortable handling large datasets, optimizing data pipelines, and delivering high-quality outputs. Leadership & Client-Facing Skills Excellent communication and storytelling skills for senior stakeholders. Demonstrated ability to lead multiple project teams and manage priorities with autonomy. Strong strategic thinking, problem-solving mindset, and drive for continuous improvement. Supportive team player with a passion for talent development, coaching, and enabling team growth. Ability to contribute to impactful thought leadership and forward-thinking perspectives on measurement and marketing effectiveness. Why join us? At Ekimetrics, your ideas matter. We embrace an entrepreneurial spirit and a collaborative environment, with a focus on safe, inclusive spaces where you can bring your authentic self. We have pursued CSR and purpose-driven work, and are committed to sustainability through data science and AI. We are proud to be recognised as a Great Place to Work in multiple regions and to be part of initiatives and communities that support growth and innovation. Career development and growth opportunities Lead projects and develop advanced analytical and client-facing skills. Structured career progression from Senior Analyst, Manager, Senior Manager and beyond. Access to Eki.Academy, including solution-specific training, Climate School courses, and career development programs. Exposure to international clients, multiple industries, and high-impact projects. Compensation and benefits Salary £60,000-£75,000 plus 10% bonus and corporate bonus. Regular events and seminars to connect with colleagues. Modern office space in a central London location. Flexible hybrid working policy (2 days in office + 20 days work from anywhere). 25 days annual leave plus bank holidays, with an additional 3 days for tenure. Private healthcare, life insurance, and wellbeing support. Group pension scheme. Opportunities for international mobility and career development. Equal employment opportunities: Ekimetrics is committed to an inclusive work environment that respects diversity and provides equal opportunity for all applicants.

Ekimetrics in London seeks a Senior Analyst specialising in Data Science & Marketing Effectiveness to lead MMM programmes for international clients. You will manage teams, oversee end-to-end delivery, and ensure actionable insights reach senior stakeholders and C-suite executives. You will build dashboards, apply econometrics and Bayesian methods, and translate complex results into practical recommendations, driving ROI and client success. Hybrid work with a central London base.

Senior/Lead Data Scientist -FraudJob detailsData ScienceLondonFull-time£81,425 GBP - £116,438 GBP What you will do We are rebuilding our fraud detection systems from the ground up, and we are looking for data scientists who want the full mandate to do it right, from raw data to production model, at a scale that affects hundreds of millions of transactions. Klarna is a big company that still moves like a startup: fast decisions, real ownership, and models that ship. We own the full stack, and expect you to build it with us to enable your use cases. If you have the curiosity to find the right problem, the grit to build the right solution, and the ambition to see it matter, this is the opportunity.Fraud is one of the most technically demanding problem spaces at Klarna. You will build best-in-class machine learning systems from the ground up, owning the complete pipeline from raw data through feature engineering, model design, training, and real-time production deployment. A central part of this role is converting some of Klarna's existing rules-based fraud systems into sophisticated, model-driven architectures that operate at scale across hundreds of millions of transactions.You will build infrastructure from scratch, not maintain or extend existing frameworks. Working with engineers, analysts, and commercial stakeholders, you will translate ambiguous business problems into precise technical solutions and bring novel approaches such as graph networks, anomaly detection, and behavioural signals into production where they create real impact. Who you are End-to-end ML ownership across the full stack: data engineering, feature development, model design, training, low-latency production deployment, monitoring, and retraining. Strong instinct for when a model is ready for production and when it is not. Proven track record of building ML models and pipelines from scratch, not integrating or extending someone else's product or tooling. Experienced building real-time or near-real-time inference systems; batch pipelines alone are insufficient. Comfortable with large-scale datasets including hundreds of millions of transactions and high-dimensional feature spaces. Strong Python and SQL skills with hands-on experience in scikit-learn, LightGBM, Docker, Jenkins, and modern Python packaging. Self-motivated, fast-moving, and creative. You bring novel solutions where others reach for off-the-shelf tooling. Communicates precisely across technical and non-technical audiences including senior stakeholders. Degree in computer science, physics, applied mathematics, astrophysics, automatic control, mathematics, software engineering, electrical engineering, or a related quantitative field. Awesome to have Experience building end-to-end ML systems in early-stage startups or small greenfield teams. This is a strong positive signal. Hands-on production experience with graph neural networks, anomaly detection, or behavioural biometrics, beyond prototyping or fine-tuning. Familiarity with AWS (SageMaker, Lambda, S3, Athena) and CI/CD practices. Experience mentoring or technically guiding other data scientists.Please include a CV in English.

Relay is fundamentally reshaping how goods move in an online era. Backed by Europe's largest-ever logistics Series A ($35M), led by deep-tech investors Plural (whose portfolio spans fusion energy and space exploration), Relay is scaling faster than 99.98% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen Relay's Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. THE TEAM 110 people, more than half in engineering, product and data 45+ advanced degrees across computer science, mathematics and operations research Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle An intellectually vibrant culture of first principles thinking, tight feedback loops and relentless experimentation About the role Relay's network runs on forecasts. Every shift released in sortation, every middle-mile van dispatched, every last-mile route planned, every expansion decision made - all downstream of models that predict how parcels move through our system. When those models are right, the network runs efficiently and cost per parcel drops. When they drift, the cost compounds across every stage of the operation. The Network squad builds and maintains the forecasting engine that powers all of it. As a Senior Data Scientist in the Network squad, you will lead a core domain within that engine, working alongside other Data Scientists and Analysts who each bring different expertise. The scope spans demand forecasting, expansion modelling, parcel intelligence, and sortation predictions - and the specific domain you take on will depend on your strengths and what the squad needs most. What's common across all of it: you will build and maintain models that directly drive operational decisions for multiple teams across Relay, every day. This means different things depending on the domain. It might mean building the expansion models that determine where Relay grows next: which outcodes to enter, how volumes ramp in new areas, and how the pitstop network should evolve. It might mean working on the dimensions model that predicts parcel weights and sizes before they arrive, feeding route planning and vehicle loading decisions. It might mean extending the demand forecast horizon from 7 days toward 30, giving downstream teams more lead time to plan. Or it might mean improving the predictions that determine what volume is available to sort on a given night, and how that volume should be allocated across sort centres. Relay operates a centralised data team of around 30 Data Engineers, Analysts, and Data Scientists, with specialists embedded into squads across the business. You will sit in the Network squad alongside other Data Scientists and Analysts, reporting into the centralised data team. The squad is growing, and you will have significant influence over its technical direction and the modelling approaches it adopts. You will be supported by Analysts who build the monitoring and reporting layer, and a squad lead who sets strategic direction. What You'll Do Build and maintain forecasting models within your domain - from initial exploration through to validation and production deployment Learn the operational processes your models serve, supported by the squad and the teams who use the forecasts, and identify where the current approach falls short Monitor how your models perform in production, investigate when accuracy drops, and work with the squad to improve them Contribute to methodology decisions and validation approaches, working with other Data Scientists in the squad to improve the forecasting engine over time Translate problems from consuming squads into data science problems - Sortation, Middle Mile, Last Mile, Routing, and Commercial each depend on Network's forecasts Work with Finance, who extend the operational forecasts into longer-range financial projections, to ensure the handoff between operational and financial models is reliable Quantify the impact of model errors on cost per parcel, helping the squad and stakeholders prioritise where to invest effort Influence the squad's technical direction and modelling approaches as the team grows Who Will Thrive in This Role? Experience thinking about interconnected systems - understanding that a demand forecast isn't just a number, but flows through shift release, van dispatch, route planning, and courier allocation. You're interested in how your models connect to the models around them. A track record of building and delivering models. You've worked from ambiguous starting points before - understanding the problem, building something useful, validating it against real operations, and iterating. You evaluate models beyond standard offline metrics - connecting outputs to downstream applications and business KPIs, and measuring how improvements translate into operational impact. The squad works collaboratively to define priorities and scope, and you'll have support from the squad lead and your peers as you ramp up Strong Python and SQL, and comfort working across the modelling lifecycle - from data extraction and feature engineering through to model training, validation, and production deployment. You've worked with time-series forecasting methods - whether classical statistical approaches, gradient boosting, deep learning, or a combination - and you understand the trade-offs between them. Experience with data engineering is useful, and you'll be supported by a dedicated engineer in the squad. You have at least 5 years of experience in a data science or quantitative modelling role, with examples of models you built that informed operational or commercial decisions. You've taken models from notebook to production - writing maintainable code, building pipelines that run reliably, and debugging when they don't. You've contributed to methodology decisions and understand that a model isn't done when it trains well; it's done when it's running, monitored, and trusted. You have experience communicating with non-technical stakeholders. The squads that consume the forecasts need to trust them, and that trust comes from explaining what the models do, where they're reliable, and where they're not. You're comfortable using AI tools - LLMs, code assistants, and similar - to accelerate your workflow, from exploratory analysis to code generation, and you're curious about where these tools can augment the modelling process itself. This role suits someone who wants to see whether their models made a real difference to how the network operates - there is a direct feedback loop between your work and operational outcomes. Logistics or delivery network experience is a plus, but what matters more is the ability to learn a complex operational domain quickly and model it well. Compensation, Benefits & Workplace Generous equity, richer than 99% of European startups, with annual top-ups to share Relay's success. Private health & dental coverage, so comprehensive you'd need to be a partner at a Magic Circle law firm to match it. 25 days of holidays Enhanced parental leave. Located in Shoreditch, our office set-up enables the kind of in-person interactions that drive impact. We work 4 days on-site, with 1 day remote. Hardware of your choice. Extensive perks (gym subsidies, cycle-to-work, Friday office lunch, covered Uber home and dinner for late nights, and more). Who Thrives at Relay? Aim with Precision: You define problems clearly and measure your impact meticulously. Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction. 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience. All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts. People-Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success. Grow the Whole Pie: You seek out win win solutions for merchants, couriers, and our customers, because when they thrive, so do we. If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let's connect. Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.

About MoonPay MoonPay is for builders with something to prove. This isn't a "work on cool crypto stuff" company. It's a high-standards, high-velocity, high-accountability company building the operating system for value movement. If the internet moves information, we move value: crypto, stablecoins, tokenized assets, and whatever comes next. Four offerings make that real: fund, tokenize, trade, and spend. 30M+ customers and 500+ ecosystem partners run on us. Licensed in the U.S. Regulated across the UK, EU, Canada, and Australia. AI is the default operating mode here. It's woven into every role, and we expect you to use it daily. It handles the manual work so you can deliver on what actually matters. You'll thrive here if outcomes excite you more than process, if impact motivates you more than titles, and if you want hard problems, real ownership, and teammates who love winning, building, and doing it together. The bar is high. The pace is real. We're building for what's next, for humans and agents. Recent recognition: Forbes' America's Best Startup Employers 2026, 2nd in Crypto Services on Fortune's inaugural Crypto 100, The Sunday Times Best Places to Work two years running. Locations Supported London, UK (primary) Remote (Europe) Relocation available: Case by case Work pattern: Remote across Europe, with hybrid working encouraged if you're near a Moonbase (around 2 to 3 days per week in the London office). About the Opportunity In this role, you'll help shape MoonPay's product and business decisions through data, combining deep analysis, experimentation, and strong stakeholder partnership to drive real impact. You'll sit within our centralised Product Data team and work closely with Product and Engineering, owning analytics across the full product lifecycle, from defining problems and success metrics through to launching, measuring, and optimising products at scale. Your work will directly influence product strategy, customer experience, and business health, helping teams make better, faster decisions through trusted insights and clear narratives. You'll also raise the leverage of the whole team by building reusable, AI-assisted analytics skills that let the wider org self-serve reliable answers. This is a great opportunity for someone who enjoys turning complex data into clear direction, influencing decisions, and helping shape the future of high-impact financial and crypto products. Responsibilities Partner with product and business teams to run rigorous analysis (root cause, opportunity sizing, funnel drop-off) and turn it into clear, prioritised recommendations, moving across problem areas as priorities shift. Define, document, and maintain clear metric definitions and business context, so stakeholders can understand the performance of their area and AI tools can interpret our metrics correctly (e.g. Transaction Success Rate, Fraud Rate). Set up tracking and monitoring for new launches and changes, and quantify and measure their impact on KPIs. Build and maintain a reporting layer, with automated alerting and root cause analysis that flags when KPIs move unexpectedly and why. Design, run, and interpret experiments, from A/B tests to quasi-experimental methods like difference-in-differences when randomisation not possible. Model robust, trusted data in our dbt and BigQuery layer, safeguarding its quality through testing, documentation, and certification in collaboration with engineering. Create reusable, AI-assisted analytics skills that scale the team's impact and help Product and Engineering self-serve. Communicate complex concepts and findings to technical and non-technical audiences across different teams, while ensuring clarity and understanding to drive critical business decisions. Requirements 5+ years of hands on experience as a data analyst or data scientist, preferably in a product focused role. Advanced SQL and data visualisation are second nature to you. Hands on experience building data models in a modern cloud warehouse and transformation framework (e.g. dbt with BigQuery, Snowflake), with a strong instinct for data quality. A solid grasp of statistics and probability, including experiment design and interpretation (A/B and quasi experimental methods such as difference in differences). A working understanding of how a payments or fintech business operates, including fraud, chargebacks, KYC/AML, and payment success rates. Comfort using AI assisted and LLM tools to accelerate analysis, and curiosity about building reusable skills that scale your impact. Exceptional communication and stakeholder skills. You can distill complex findings for any audience up to C level, and lead projects independently. Nice to Have Familiarity with our stack (dbt, BigQuery, Looker, Python) and AI tooling such as Claude Code. Hands on financial crime, payments, or fraud analytics experience. Experience working in start ups or scale ups. A crypto native perspective and experience with on chain and blockchain data (e.g. Dune, Flipside, Chainalysis). Experience making data self serve for non analysts (e.g. semantic layers, metric stores). Benefits & Perks Competitive salary package Equity package: financial freedom starts with our employees, so all employees have ownership at MoonPay Pay for performance equity bonus: those who drive outsized outcomes receive outsized rewards Moonshot award: we honor exceptional impact. 10 employees twice a year, each earning a $250,000 equity grant Pension: employer contributions from day one Employee referral program: refer great people, earn 10K in USDC Flexible Time Off: choose when to work and when to switch off Birthday leave: take the day off to celebrate you Enhanced parental leave: more time with family, no second thought Hybrid working schedule: work fully remotely or from your nearest Moonbase Commuter benefits: public transport to and from the office Private healthcare benefits: to protect you and your loved ones Wellhub wellness membership: access to gyms, studios, classes, and wellness apps in one membership Unlimited enterprise access to the latest AI tools: Claude, ChatGPT, Gemini and whatever's next Lunch credit: meals covered on the days you're in the office Home office setup allowance: build the home office of your dreams Remote working allowance: those working fully remotely get a little extra for utilities Monthly product budget and zero fee crypto transactions $1,000 Annual training budget: we support your learning journey High Potential Program: structured development, mentorship, and stretch opportunities Regular remote company offsites: high impact in person sessions and hackathons (Ireland) Cycle to Work scheme: tax efficient bike, gear, and safety kit (UK) EV Salary Sacrifice: lease an electric vehicle through pre tax salary

Tripledot Studios is one of the largest independent mobile games companies in the world. We are a multi-award-winning organisation, with a global 2,500+ strong team across 12 studios. Our expanded portfolio includes some of the biggest titles in mobile gaming, collectively reaching top chart positions around the world and engaging over 25 million daily active users. Tripledot's guiding principle is that when people love what they do, what they do will be loved by others. We're building a company we're proud of. One filled with driven, incredibly smart and detail-orientated people, who LOVE making games. Our ambition is to be the most successful games company in the world, and we're just getting started. Group role reporting to the IT team The role will focus on AI/ML infrastructure for various group use cases from proprietary models training to efficient 3rd party tool running environments etc. This role will be working with all Group central teams (Marketing, Finance, HR, AI, IT). Role Overview You will build and maintain the high-performance infrastructure required to train and deploy AI models that impact millions of players in real-time, as well as improve productivity of everyone at Tripledot. You will serve as a bridge between the technical solutions that are created by our teams and our live game engines, as well as creating and maintaining infrastructure for internal IT needs. Within the group AI functions you'll be working with other AI / ML engineers, data engineers, analysts and product owners. Within the various studios and other central teams, you will interact with data, engineering, and product teams. Within group IT, you'll partner with Engineering, TechOps, and Security to deliver the infrastructure and tooling that powers our central business functions: gaming, finance, marketing, legal, people ops, and beyond. The first initiative you'll be taking part of is the expansion of a data/ML Platform to support ML engineers and data scientists to easily deploy their solutions, and enabling delivery of key projects like LTV and Ads Optimization. Key Responsibilities Improve and maintain a scalable, speedy and reliable data and ML platform to support AI/ML initiatives within group AI, ensuring models move seamlessly from research to production. Support group IT to provide reliable access to open source AI models and ensure safe reliable access to AI productivity tools. Create and maintain proper monitoring and alerting tools to ensure our systems can provide the correct SLA and SLOs defined by the stakeholders. Implement and advocate for engineering best practices, including CI/CD, infrastructure as code like Terraform, usage of version control, testing, observability, while keeping costs in mind. Ensure standardized cross-studio access & security to enable timely data access and ingestion (AWS and Google Cloud). Enable the teams with different environments for testing new setups, tools, without disrupting the day-to-day operations of the team and production workflows. Track usage for all our deployed applications, and identify areas of improvement, making the best use of resources. Keep up with the relevant technologies, best practices, especially related to AI productivity tools, continuously emerging in the industry. What we are looking for 5+ years in the industry as a DevOps, SRE Engineer or or Platform Engineer, ideally in gaming, mobile apps, or other high-scale digital products. Strong hands on experience with Kubernetes in production - not just running workloads on it, but operating it. Cost aware infrastructure decision making. Solid Terraform (or OpenTofu) experience, with a track record of keeping IaC sustainable as it grows. Proven experience in delivering data and AI/ML solutions in production for both AWS and a working knowledge of GCP or willingness to come to speed quickly. Bonus if this experience is within the gaming industry. Comfortable owning CI/CD pipelines with common tools (GitHub Actions, GitLab CI, ArgoCD, Jenkins, or similar). Hands on experience with cloud and Kubernetes security fundamentals, IAM/RBAC, secrets management (ex. Vault, AWS Secrets Manager, External Secrets), network policies, and integrating security checks into CI/CD pipelines. Strong instincts for observability, monitoring, and alerting, you've built dashboards and alerts that teams actually rely on, and you know the difference between a useful page and noise. Hands on with tools like Prometheus, Grafana, Datadog, CloudWatch, or similar. Solid incident response experience. The current data and AI/ML stack uses open source tools like Airflow, Trino, Spark, and Kubeflow. Familiarity with deploying these tools, as well as tweaking them for improved performance, is a bonus. Understanding of ML Ops best practices and common architectures is also a bonus. Hands on knowledge of Python and/or other scripting languages. Experience creating infrastructure for both traditional and modern agentic data intensive systems is a bonus. Focus on innovation, coupled with a mindset of continuous learning and curiosity to explore emerging AI technologies. The successful candidate will have an agile, hands on approach to prototyping and validation, and ability to Get Stuff Done in a fast paced environment. Excellent communication and collaboration skills necessary for working effectively with both technical and non technical teams. Understanding how to drive results with key business stakeholders. You will be part of a fun mobile gaming company aiming to embrace the future of AI driven creativity and exploring where the industry is moving. You will be instrumental in shaping the backbone of the AI/ML and IT systems that will power solutions that will spread throughout the whole group. You will operate in an environment that values an experimental mindset, focusing on learning opportunities and pioneering generative game creation. Working at Tripledot (in London) 25 days holiday: Enjoy 25 days of paid holiday, in addition to bank holidays to relax and refresh throughout the year. Hybrid Working: We work in the office 3 days a week, Tuesdays and Wednesdays, and a third day of your choice. 20 days fully remote working: Work from anywhere in the world, 20 days of the year. Regular company events and rewards: Join in regular events and rewards that celebrate cultural events, our achievements and our team spirit. Recent highlights have been: Thames River Cruise, London Dungeon and Summer Parties in Regents Park. Continuous Professional Development: Propel your career with continuous opportunities for professional development. Private Medical Cover: Have peace of mind with private medical cover, ensuring your health is in good hands. Life Assurance & Critical Illness Cover: Financial protection for you and your loved ones. Health Cash Plan: Benefit from a health cash plan that contributes to your medical expenses. Dental Cover: Flash your best smile with our dental cover. Family Forming Support: Receive vital support on your family forming/ fertility journey with our support program subject to policy Employee Assistance Program: Anytime you need it, tap into confidential, caring support with our Employee Assistance Program, always here to lend an ear and a helping hand. Cycle to Work Scheme: Make the most of our Cycle to Work Scheme for a green and healthy commute. Pension Plan: Secure your future with our contributory pension plan.

About 9fin 9fin is the AI platform powering global debt markets - the world's largest asset class at over $145 trillion. Debt markets are vast, global, and mission-critical, yet still run on fragmented data, PDFs, and manual workflows. 9fin replaces this broken infrastructure with a single platform that centralises proprietary credit data, deep analysis, and high-value workflows across global markets. Today, 9fin powers teams at 300+ blue-chip institutions worldwide, including global banks, asset managers, private equity firms, law firms, and advisors. The business is scaling at exceptional speed, with rapid expansion in the US and best-in class retention driven by deep workflow adoption. We're at a defining inflection point. With proven product market fit and strong, global market pull, 9fin is accelerating toward becoming the category defining platform for debt markets worldwide. The Opportunity Our AI product area is growing. We already have two Product Managers working across conversational AI, agentic workflows, and domain specific automation, and we need a third to expand our capacity as the scope of AI at 9fin accelerates. Backed by over $170M in funding (Series C), we are scaling rapidly across product, engineering, and go to market. AI is not a bolt on feature at 9fin; it is the core differentiator for the next phase of the company. You will join an established AI PM team and take ownership of a product area within our AI surface. This could span new AI powered features for credit analysts, workflow automation for legal and financial analysis, or expanding our conversational AI into new domains. The team has already built evaluation infrastructure and quality frameworks; you will use and contribute to these rather than build them from scratch. You will work within our product organization (eight squads across AI, data, and domain verticals) and partner closely with ML engineers, data scientists, domain experts, and designers. This is a high autonomy role with real scope to shape what 9fin's AI products can do for our clients. What You'll Do Product Strategy & Execution Collaboratively create and champion a clear product vision and strategy for your area, with a focus on building and evolving our AI products Synthesize qualitative and quantitative insights into problem statements that identify root causes, not just symptoms Shape the next generation of agentic AI products: multi step reasoning workflows, tool orchestration, and autonomous task completion for financial professionals Demonstrate a working understanding of the challenges specific to building with LLMs, including managing hallucinations, evaluating output quality, and designing for non deterministic systems Use confidence building methods (prototypes, user research, data analysis) to understand how users will interact with AI powered products before committing to full builds AI Quality & Data Use the team's AI evaluation framework (LLM as judge protocols, quality thresholds, SME eval cycles) to validate and improve the products you ship Contribute to the data strategy for your product area: annotation quality, ground truth curation, and feedback loops that improve model performance over time Proactively identify and track metrics that measure client and business benefit, working with the team on continuous model evaluation and improvement Team Leadership & Communication Create a collaborative environment for your squad, providing wider context and clear goals so everyone can do their best work Work with data scientists and ML engineers to bridge the gap between business needs and the technical capabilities of AI models Communicate strategy, initiatives, and progress transparently across the organisation Translate complex AI concepts, capabilities, and limitations into language that non technical stakeholders can act on Champion responsible AI practices: transparency in model outputs, bias monitoring, and compliance with client expectations around AI generated content What We're Looking For 5+ years of product management experience, preferably in FinTech or B2B SaaS, with at least 2 years focused on ML or GenAI products Working knowledge of RAG architectures, embeddings, prompt engineering, and LLM evaluation methods (not just "AI concepts" at a high level) Experience shipping AI products where output quality is probabilistic: you know how to define "good enough" and iterate from there Comfortable reading Python notebooks and SQL to interrogate model outputs and usage data Track record of shipping AI products where you managed the tension between ML research/exploration and production delivery constraints Collaborative leadership style with strong stakeholder management; you build relationships that empower your team to achieve outcomes User centric communication skills: you can explain AI capabilities and limitations to clients and internal stakeholders without overselling or underselling You thrive in fast paced, ambiguous environments and are energised by the challenge of building something new Nice to Have Experience in financial services, legal tech, or data/analytics platforms Familiarity with credit markets, debt instruments, or regulatory/compliance workflows Experience with NLP applied to document analysis (contracts, legal filings, financial reports) Experience with agent orchestration frameworks, tool use patterns, or multi step AI workflows Benefits Competitive, market benchmarked salary Pension with 7% company matching Private medical insurance, paid sick leave, income protection, group life assurance Season ticket and cycle to work schemes Hybrid flexibility with up to 3 months annual work abroad 25 holiday days plus local public holidays (exchangeable) One month paid sabbatical after 5 years; enhanced parental leave Professional development budget and regular social events 9fin is an equal opportunities employer At 9fin we are dedicated to building and promoting a fair and inclusive workplace where everyone can reach their full potential and truly belong. We recognize that building diverse teams enables a more creative and productive environment. If you're excited about this role but your experience doesn't perfectly align with the job description, we encourage you to apply anyway. You might just be who we're looking for - either for this role, or perhaps another.

We're looking for a Senior Analytics Platform Engineer. In this role you will help shape the future of data at Our Future Health by building the foundations that power trusted, scalable analytics across the organisation. As a Senior Analytics Platform Engineer, you'll design and maintain analytics ready data products that enable consistent, reliable insight at scale. You'll work across the analytics platform, data product teams, and scientific users to improve how data is modelled, documented, and adopted, while also coaching others to build high quality analytical assets with confidence. This is a role where your impact multiplies, success means everyone can build better analytics, not just you. At Our Future Health, our mission is to transform the prevention, detection and treatment of conditions such as dementia, cancer, diabetes, heart disease and stroke. We're looking for people to join us on our journey. If you're looking for a new challenge where you can contribute to helping future generations live in good health for longer, then we're keen to speak with you. What you'll be doing Designing and maintaining analytics ready data models in Snowflake using dbt, including data marts, metrics, and reusable analytical datasets. Applying scalable modelling patterns and contributing to organisation wide standards and conventions. Coaching analysts, data scientists, and science teams in analytics engineering best practice, modelling, testing, documentation, and data quality. Enabling domain teams to own and maintain their data marts safely and confidently, with guidance and review to ensure alignment with platform standards. Partnering with internal researchers to translate exploratory analysis into repeatable, well modelled datasets with clear definitions and reproducible insights. Shaping analytical products around real use cases, ensuring data marts are intuitive, discoverable, and fit for purpose. Owning data quality at the analytics layer, using dbt tests, monitoring, and close collaboration with platform engineers to resolve issues. Building and maintaining the semantic layer in Snowflake and Omni to support consistent, self serve analytics. Supporting adoption of Omni through documentation, examples, and hands on guidance. Collaborating with data product teams on ingestion, data contracts, and quality expectations. Working closely with Analytics Platform Engineers on dbt execution patterns, performance optimisation, and CI/CD improvements. Mentoring mid level analytics engineers and contributing to a culture of high quality, scalable analytics. What you won't be doing Working in a siloed environment with no freedom to make decisions. Working in a place where you can't see the impact your expertise makes. To succeed in this role you will be able to demonstrate some of the following skills and experience: Proven analytics engineering experience with a track record of building analytics ready datasets. Python engineering ability to produce clean, maintainable, production grade code. Hands on dbt expertise including modelling, testing, documentation, and data quality. Understanding of metrics and KPIs and how to translate them into well structured data models. Experience working with analysts and data scientists to support and enable analytical work. Clear, empathetic communication to explain modelling decisions to non engineers. A coaching mindset that helps domain teams take ownership of their models. Strong analytical problem solving with a focus on clarity, simplicity, and maintainability. Comfort navigating complex data ecosystems and shaping standards across teams. Interest in platform level concerns such as performance, orchestration, CI/CD, and reliability. Experience with cloud native tooling including Kubernetes and containers. Familiarity with semantic layers such as Snowflake, Omni, or Looker. Experience in regulated or scientific environments where governance and reproducibility matter. Salary from £80,000 per annum. Generous Pension Scheme - We invest in your future with employer contributions of up to 12%. 30 Days Holiday + Bank Holidays - Enjoy a generous holiday allowance with the flexibility to take bank holidays when it suits you. Enhanced Parental Leave - Supporting you during life's biggest moments. Cycle to Work Scheme - Save 25-39% on a new bike and accessories through salary sacrifice. Home & Tech Savings - Get up to 8% off on IKEA and Currys products, spreading the cost over 12 months through salary sacrifice £1,000 Employee Referral Bonus - Know someone amazing? Get rewarded for bringing them on board! Wellbeing Support - Access to Mental Health First Aiders, plus 24/7 online GP services and an Employee Assistance Programme for you and your family. A Great Place to Work - We have a lovely Central London office in Holborn, and offer flexible and remote working arrangements. Join us - let's prevent disease together. At Our Future Health, we recognise the importance of having a diverse workforce and ensuring that all candidates, regardless of their background, have equitable access to our application process. We proactively encourage applicants who identify as having a disability, neurodiversity, or long term health conditions to let us know if they require any reasonable adjustments as part of their application process. If you do require any reasonable adjustments, please email us at

Relay is fundamentally reshaping how goods move in an online era. Backed by Europe's largest-ever logistics Series A ($35M), led by deep-tech investors Plural (whose portfolio spans fusion energy and space exploration), Relay is scaling faster than 99.98% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen Relay's Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. THE TEAM 110 people, more than half in engineering, product and data 45+ advanced degrees across computer science, mathematics and operations research Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle An intellectually vibrant culture of first principles thinking, tight feedback loops and relentless experimentation Work Alongside Industry Leaders Karthik Harith - VP Operations Karthik is an operator and GM with a track record scaling multi-channel retail and operations across the UK, Germany, and France. Prior to Relay, he operated at VP/General Manager across multiple markets and brands (Getir, Gorillas, and Frichti). He holds a BS in Electrical Engineering (Brown) and an MBA in Finance (HEC Paris). At Relay, Karthik leads Operations, bringing rigorous execution and scaling experience to solve hard, real world logistics problems end to end. Relay's Mission Relay exists to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. The Opportunity Relay's network runs on forecasts. Every day, models predict how many parcels will arrive, which ones to sort tonight, how many shifts to release, and how many bags each route needs. The Network squad owns those forecasts and the operational processes that turn them into action. When teams plan to the right number, the network runs efficiently. When they over plan, capacity goes to waste; when they under plan, cost surges and operational performance suffers. At a high level, the outcome you will drive is excellent day to day forecast guidance-ensuring teams across the network plan to the right number every day. This is one of the most powerful cost levers in the business. As Senior Operations Associate, you will own the day to day operational processes that drive this outcome. You will be the squad's operational backbone: the person who keeps the network on track, steps in when things break, and coordinates the right teams when the operation is under stress. This is fundamentally an operational role-high-context, high ownership, and central to how the network runs every day. Alongside the day to day execution, you will have the opportunity to keep critical projects moving forward across the squad. As a Senior Operations Associate, Network at Relay at Relay, you'll: Own the quality of day to day forecast guidance. Co build and operate the systems that decide how much volume flows through our network every day, ensuring teams plan to the right number-neither over nor under planning. Continually improve these systems, partner with other Operations teams to resolve issues, and maintain a clear specification for Data and Engineering to automate further as resources become available. Plan the business through scheduled operational moments. When demand is going to deviate from the norm-busy shopping periods, holidays, planned promotions-you will develop the operational plan and make sure all relevant teams are prepared, aligned, and acting on the same source of truth. Lead the response to unplanned incidents. When something disrupts the network-adverse weather, supply side shocks, or unexpected client behaviour-you will step in to own the recovery and run the retro process to ensure follow ups are actioned. Work shoulder to shoulder with the data team. When forecasts look off or operations flag a problem, you will dig into the numbers, interrogate the models, and help the Data Scientists and Analysts pinpoint where the models are creating real world friction. You will not be building the models- but you will be a trusted partner in pressure testing them. Help keep the squad's programme of work on track-beginning with coordination and follow up, and growing into a role that guides what the squad prioritises as you build context and credibility. Who Will Thrive in this role? Resilience and high ownership. You enjoy being at the centre of how the network runs each day. The work spans daily execution and complex, ambiguous problem solving, and you take real pride in owning the outcome of both- including stepping in when other teams or processes need support. Project literacy. You have run projects or worked closely with Programme Managers in prior roles. You're comfortable absorbing the administrative scaffolding of a programme without requiring a senior PM to direct you. A bias for action. You would rather get something working today than design the perfect solution for next quarter. You know when to elevate and when to just fix it. Strong written communication. At Relay, a well structured doc or one pager is often how you get things done- it's how you align people, define problems, and create momentum without a meeting. 3-5 years of experience in operations, programme management, consulting, or a similar function-ideally somewhere fast moving where the playbook was being written in real time. Data literacy. Comfortable with SQL and able to query data independently to investigate operational issues. You can articulate the data and insight you need with sufficient clarity that an AI agent or analyst can act on it. You don't need to be building dashboards yourself - but you should be capable of pulling your own numbers when you need to. The qualifications and experiences above act as a loose guide to what we're looking for. We'd still love to hear from you if you have more or less experience, so long as the core skills can be demonstrated. Fast and Focused Hiring Process Talent Acquisition Interview - 30 min Hiring Manager Interview - 45 min Case Exercise - 90 min Final Interview w/ VP Operations - 30 min Decision and offer within 48 hours, our process mirrors our pace of work, typically completed in a week. Who Thrives at Relay? Aim with Precision: You define problems clearly and measure your impact meticulously. Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction. 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience. All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts. People Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success. Grow the Whole Pie: You seek out win win solutions for merchants, couriers, and our customers, because when they thrive, so do we. If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let's connect. Relay is an equal opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.

Relay is fundamentally reshaping how goods move in an online era. Backed by Europe's largest-ever logistics Series A ($35M), led by deep-tech investors Plural (whose portfolio spans fusion energy and space exploration), Relay is scaling faster than 99.98% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen Relay's Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. THE TEAM 110 people, more than half in engineering, product and data 45+ advanced degrees across computer science, mathematics and operations research Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle An intellectually vibrant culture of first principles thinking, tight feedback loops and relentless experimentation Work Alongside Industry Leaders Karthik Harith - VP Operations Karthik is an operator and GM with a track record scaling multi-channel retail and operations across the UK, Germany, and France. Prior to Relay, he operated at VP/General Manager across multiple markets and brands (Getir, Gorillas, and Frichti). He holds a BS in Electrical Engineering (Brown) and an MBA in Finance (HEC Paris). At Relay, Karthik leads Operations, bringing rigorous execution and scaling experience to solve hard, real world logistics problems end to end. Relay's Mission Relay exists to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. The Opportunity Relay's network runs on forecasts. Every day, models predict how many parcels will arrive, which ones to sort tonight, how many shifts to release, and how many bags each route needs. The Network squad owns those forecasts and the operational processes that turn them into action. When teams plan to the right number, the network runs efficiently. When they over plan, capacity goes to waste; when they under plan, cost surges and operational performance suffers. At a high level, the outcome you will drive is excellent day to day forecast guidance-ensuring teams across the network plan to the right number every day. This is one of the most powerful cost levers in the business. As Senior Operations Associate, you will own the day to day operational processes that drive this outcome. You will be the squad's operational backbone: the person who keeps the network on track, steps in when things break, and coordinates the right teams when the operation is under stress. This is fundamentally an operational role-high-context, high ownership, and central to how the network runs every day. Alongside the day to day execution, you will have the opportunity to keep critical projects moving forward across the squad. As a Senior Operations Associate, Network at Relay at Relay, you'll: Own the quality of day to day forecast guidance. Co build and operate the systems that decide how much volume flows through our network every day, ensuring teams plan to the right number-neither over nor under planning. Continually improve these systems, partner with other Operations teams to resolve issues, and maintain a clear specification for Data and Engineering to automate further as resources become available. Plan the business through scheduled operational moments. When demand is going to deviate from the norm-busy shopping periods, holidays, planned promotions-you will develop the operational plan and make sure all relevant teams are prepared, aligned, and acting on the same source of truth. Lead the response to unplanned incidents. When something disrupts the network-adverse weather, supply side shocks, or unexpected client behaviour-you will step in to own the recovery and run the retro process to ensure follow ups are actioned. Work shoulder to shoulder with the data team. When forecasts look off or operations flag a problem, you will dig into the numbers, interrogate the models, and help the Data Scientists and Analysts pinpoint where the models are creating real world friction. You will not be building the models- but you will be a trusted partner in pressure testing them. Help keep the squad's programme of work on track-beginning with coordination and follow up, and growing into a role that guides what the squad prioritises as you build context and credibility. Who Will Thrive in this role? Resilience and high ownership. You enjoy being at the centre of how the network runs each day. The work spans daily execution and complex, ambiguous problem solving, and you take real pride in owning the outcome of both- including stepping in when other teams or processes need support. Project literacy. You have run projects or worked closely with Programme Managers in prior roles. You're comfortable absorbing the administrative scaffolding of a programme without requiring a senior PM to direct you. A bias for action. You would rather get something working today than design the perfect solution for next quarter. You know when to elevate and when to just fix it. Strong written communication. At Relay, a well structured doc or one pager is often how you get things done- it's how you align people, define problems, and create momentum without a meeting. 3-5 years of experience in operations, programme management, consulting, or a similar function-ideally somewhere fast moving where the playbook was being written in real time. Data literacy. Comfortable with SQL and able to query data independently to investigate operational issues. You can articulate the data and insight you need with sufficient clarity that an AI agent or analyst can act on it. You don't need to be building dashboards yourself - but you should be capable of pulling your own numbers when you need to. The qualifications and experiences above act as a loose guide to what we're looking for. We'd still love to hear from you if you have more or less experience, so long as the core skills can be demonstrated. Fast and Focused Hiring Process Talent Acquisition Interview - 30 min Hiring Manager Interview - 45 min Case Exercise - 90 min Final Interview w/ VP Operations - 30 min Decision and offer within 48 hours, our process mirrors our pace of work, typically completed in a week. Who Thrives at Relay? Aim with Precision: You define problems clearly and measure your impact meticulously. Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction. 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience. All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts. People Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success. Grow the Whole Pie: You seek out win win solutions for merchants, couriers, and our customers, because when they thrive, so do we. If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let's connect. Relay is an equal opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.

About Charlotte Tilbury Beauty Founded by British makeup artist and beauty entrepreneur Charlotte Tilbury MBE in 2013, Charlotte Tilbury Beauty has revolutionised the face of the global beauty industry by de-coding makeup applications for everyone, everywhere, with an easy-to-use, easy-to-choose, easy-to-gift range. Today, Charlotte Tilbury Beauty continues to break records across countries, channels, and categories and to scale at pace. Over the last 10 years, Charlotte Tilbury Beauty has experienced exceptional growth and is one of the most talked about brands in the beauty industry and beyond. It has become a global sensation across 50 markets (and growing), with over 2,300 employees globally who are part of the Dream Team making the magic happen. Today, Charlotte Tilbury Beauty is a truly global business, delivering market-leading growth, innovative retail and product launches fuelled by industry-leading tech - all with an internal culture of embracing challenges, disruptive thinking, winning together, and sharing the magic. The energy behind the brand is infectious, and as we grow, we are always looking for extraordinary talent who want to be part of this our success and help drive our limitless ambitions. About the role Data is at the heart of our strategy to engage and delight our customers, and we are determined to harness its power to go as far as we can to deliver a euphoric, personalised experience that they'll love. Our Data Analytics team is central to these efforts and works closely with our brilliant team of Data Engineers, Data Scientists, Software Engineers and Products teams (among others) to deliver robust insights and reporting to the entire company. Everyone in the data team plays a key role in creating the foundations for robust data and empowering individuals across the business to make insightful, data-led decisions. We primarily use Snowplow, GA4 and Google Tag Manager (for our Web data), BigQuery (for our data warehousing) and Looker (for our BI and Data Visualisation). As a Senior Digital Implementation Analyst (App & Web) you will Own and maintain digital tracking implementation across app and web, primarily in Snowplow and GTM Partner closely with Product and Engineering teams to ensure new features, customer journeys, and experiments are measured clearly and consistently. Maintain and quality-assure GTM configurations, including relevant third-party tags. Gather measurement and reporting requirements from stakeholders and translate them into clear tracking, QA, and reporting-ready implementation requirements. Work with analysts, engineers, and data partners to ensure events are tracked, validated, and modelled appropriately for reporting and analysis. Support teams in understanding and using web and app reports effectively. Build strong stakeholder relationships through requirements gathering, implementation guidance, knowledge sharing, and measurement support. Maintain clear tracking documentation, event definitions, and implementation knowledge to support scalable reporting and consistent ways of working. Use modern tools, including AI-assisted workflows where appropriate, to improve efficiency, documentation quality, QA, and problem-solving. Who you will work with Data Team and many other departments About you Advanced experience in digital tracking implementation across app and web, including Google Tag Manager, data layer design, event QA, and ideally hands-on Snowplow experience. Experience with server-side tagging, or a strong understanding of server-side implementation approaches, is desirable. Experience working with BI and reporting platforms such as Looker, including translating measurement needs into clear and usable reporting outputs. Be comfortable working with event-level data in BigQuery and partnering with Data Engineers to shape reporting-ready data models. Be flexible, collaborative, and comfortable working in small teams on fast-moving and time-bound priorities. SQL experience is highly desirable, especially for validation, investigation, and working with event-level data. Be curious, proactive, and motivated to keep learning in a fast-changing measurement and analytics environment. Enjoy sharing ideas, collaborating with peers, and helping others understand data and measurement clearly. Be able to work independently, use initiative, and solve complex implementation or measurement problems with limited direction. Be able to prioritise effectively and stay organised in a fast-paced environment with competing stakeholder needs. Why join us? Be a part of this values driven, high growth, magical journey with an ultimate vision to empower everyone, everywhere to be the best version of themselves. We're a hybrid model with flexibility, allowing you to work how best suits you. 25 days holiday (plus bank holidays) with an additional day to celebrate your birthday. Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey. Financial security and planning with our pension and life assurance for all. Wellness and social benefits including Medicash, Employee Assist Programs and regular social connects with colleagues. Bring your fury friend to work with you on our allocated dog friendly days and spaces and not to forget our generous product discount and gifting!

About Charlotte Tilbury Beauty Founded by British makeup artist and beauty entrepreneur Charlotte Tilbury MBE in 2013, Charlotte Tilbury Beauty has revolutionised the face of the global beauty industry by de-coding makeup applications for everyone, everywhere, with an easy-to-use, easy-to-choose, easy-to-gift range. Today, Charlotte Tilbury Beauty continues to break records across countries, channels, and categories and to scale at pace. Over the last 10 years, Charlotte Tilbury Beauty has experienced exceptional growth and is one of the most talked about brands in the beauty industry and beyond. It has become a global sensation across 50 markets (and growing), with over 2,300 employees globally who are part of the Dream Team making the magic happen. Today, Charlotte Tilbury Beauty is a truly global business, delivering market-leading growth, innovative retail and product launches fuelled by industry-leading tech - all with an internal culture of embracing challenges, disruptive thinking, winning together, and sharing the magic. The energy behind the brand is infectious, and as we grow, we are always looking for extraordinary talent who want to be part of this our success and help drive our limitless ambitions. About the role Data is at the heart of our strategy to engage and delight our customers, and we are determined to harness its power to go as far as we can to deliver a euphoric, personalised experience that they'll love. Our Data Analytics team is central to these efforts and works closely with our brilliant team of Data Engineers, Data Scientists, Software Engineers and Products teams (among others) to deliver robust insights and reporting to the entire company. Everyone in the data team plays a key role in creating the foundations for robust data and empowering individuals across the business to make insightful, data-led decisions. We primarily use Snowplow, GA4 and Google Tag Manager (for our Web data), BigQuery (for our data warehousing) and Looker (for our BI and Data Visualisation). As a Senior Digital Implementation Analyst (App & Web) you will Own and maintain digital tracking implementation across app and web, primarily in Snowplow and GTM Partner closely with Product and Engineering teams to ensure new features, customer journeys, and experiments are measured clearly and consistently. Maintain and quality-assure GTM configurations, including relevant third-party tags. Gather measurement and reporting requirements from stakeholders and translate them into clear tracking, QA, and reporting-ready implementation requirements. Work with analysts, engineers, and data partners to ensure events are tracked, validated, and modelled appropriately for reporting and analysis. Support teams in understanding and using web and app reports effectively. Build strong stakeholder relationships through requirements gathering, implementation guidance, knowledge sharing, and measurement support. Maintain clear tracking documentation, event definitions, and implementation knowledge to support scalable reporting and consistent ways of working. Use modern tools, including AI-assisted workflows where appropriate, to improve efficiency, documentation quality, QA, and problem-solving. Who you will work with Data Team and many other departments About you Advanced experience in digital tracking implementation across app and web, including Google Tag Manager, data layer design, event QA, and ideally hands-on Snowplow experience. Experience with server-side tagging, or a strong understanding of server-side implementation approaches, is desirable. Experience working with BI and reporting platforms such as Looker, including translating measurement needs into clear and usable reporting outputs. Be comfortable working with event-level data in BigQuery and partnering with Data Engineers to shape reporting-ready data models. Be flexible, collaborative, and comfortable working in small teams on fast-moving and time-bound priorities. SQL experience is highly desirable, especially for validation, investigation, and working with event-level data. Be curious, proactive, and motivated to keep learning in a fast-changing measurement and analytics environment. Enjoy sharing ideas, collaborating with peers, and helping others understand data and measurement clearly. Be able to work independently, use initiative, and solve complex implementation or measurement problems with limited direction. Be able to prioritise effectively and stay organised in a fast-paced environment with competing stakeholder needs. Why join us? Be a part of this values driven, high growth, magical journey with an ultimate vision to empower everyone, everywhere to be the best version of themselves. We're a hybrid model with flexibility, allowing you to work how best suits you. 25 days holiday (plus bank holidays) with an additional day to celebrate your birthday. Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey. Financial security and planning with our pension and life assurance for all. Wellness and social benefits including Medicash, Employee Assist Programs and regular social connects with colleagues. Bring your fury friend to work with you on our allocated dog friendly days and spaces and not to forget our generous product discount and gifting!

Relay is fundamentally reshaping how goods move in an online era. Backed by Europe's largest-ever logistics Series A ($35M), led by deep-tech investors Plural (whose portfolio spans fusion energy and space exploration), Relay is scaling faster than 99.98% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen Relay's Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. Team 110 people, more than half in engineering, product and data 45+ advanced degrees across computer science, mathematics and operations research Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle An intellectually vibrant culture of first principles thinking, tight feedback loops and relentless experimentation The Opportunity Relay's Network squad builds the forecasting engine that powers every operational decision in the business. Demand forecasts drive shift release in sortation. Expansion models determine where the network grows. Parcel intelligence feeds route planning and vehicle loading. When the squad ships a better model, the impact multiplies across five consuming squads, Finance, and ultimately Relay's cost per parcel. The squad is growing from four people to ten: Data Scientists, Analysts, and a Software Engineer, each contributing to a system that spans demand forecasting, expansion modelling, parcel dimensions, sortation predictions, and demand management. That system has dependencies on Sortation, Middle Mile, Last Mile, Routing, and Commercial - plus Finance, who extend the operational forecasts into longer-range financial projections. It also supports four embedded analysts sitting in other squads across the business. As Programme Manager for the Network squad, you coordinate the delivery of this system. The role involves taking the squad's roadmap and turning it into a structured programme - tracking commitments, managing cross-squad dependencies, removing blockers, and keeping stakeholders informed. The specifics of the programme will develop as you ramp up and learn how the squad and its consuming teams work together. The squad lead sets technical direction and manages people. You work alongside them to keep the programme on track, supported by a team that values coordination and wants to deliver well. Relay operates a centralised data team of around 30 data engineers, analysts, and data scientists. The Network squad sits within this team and serves every operational squad in the business. You will work with the squad lead, the Data Scientists and analysts in the squad, and the leads of the five consuming squads. What You'll Do Coordinate the delivery programme for the Network squad: roadmap tracking, sprint management, cross-squad coordination, and dependency management across a 10-person team Manage dependencies with five consuming squads (Sortation, Middle Mile, Last Mile, Routing, Commercial) and Finance, ensuring that what Network delivers matches what those teams need and when they need it Run the squad's delivery cadence: cycle planning, triage, standups, retros, and cross-functional syncs Track commitments and surface risks early - identifying which initiatives are on track, which are slipping, and what needs to change Remove blockers that sit outside the squad: engineering dependencies, data access, stakeholder alignment, prioritisation conflicts with other squads Coordinate the work of four embedded analysts in other squads (Routing, Sortation, Middle Mile, and one TBC), ensuring alignment with Network's priorities Keep stakeholders informed with regular updates on what's shipped, what's in progress, and what's changed Support the squad lead by taking on operational coordination, freeing them to focus on technical direction, model quality, and strategic relationships Who Will Thrive in This Role? You have at least 5 years of experience in programme management, delivery management, or a similar coordination role, ideally in a technical or data-heavy environment. You have experience managing multiple workstreams. You have experience working in technical environments even if you're not a data scientist yourself. You can follow a conversation about model accuracy, forecast horizons, and pipeline reliability enough to know when something is blocked, behind, or being under-scoped. The squad will help you build domain knowledge as you ramp up. You have experience tracking commitments and following up when things stall. You bring structure to how teams track and deliver their work. You have experience coordinating across teams without direct authority - helping squads understand what's expected and when. You have experience communicating with stakeholders at different levels - giving a squad lead a quick update on a dependency, giving senior leadership a picture of the programme's health, and giving a Data Scientist an answer on when their work will be prioritised. You have experience managing dependencies and how work connects across teams. You plan for how one squad's timeline affects another's. Experience in logistics, data platforms, or forecasting environments is a plus, but what matters more is the ability to learn a complex technical domain quickly and manage a programme within it effectively. Who Thrives at Relay? Aim with Precision: You define problems clearly and measure your impact meticulously. Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction. 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth. You move quickly, deliver results, and learn from every experience. All In, All the Time: You show up and step up. You take ownership from start to finish and do what it takes to deliver when it counts. People-Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success. Grow the Whole Pie: You seek out win win solutions for merchants, couriers, and our customers, because when they thrive, so do we. If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let's connect. Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.

Our Borrowing Analytics Engineering Team: Our Mission in Borrowing is to enable people's financial goals through better borrowing. Our customers look to borrow money to enable them to achieve something in their lives - whether that's making a big life event affordable, buying something they need now without affecting their monthly budget, or getting by until payday. And we're looking to shape this mission by building products that our customers love, whilst scaling those top revenue lines across the business safely. We're looking for a Lead Analytics Engineer within our borrowing team to help build world class service for the bank of the future. You will play a critical role in overseeing our foundational data platforms, identifying and driving opportunities to enhance our current capabilities. Your expertise will be pivotal in allowing us to scale into new global markets, build new products and shape the future of how we serve our customers. We have a strong culture of data-driven decision making across the whole company. And we're great believers in powerful, real-time analytics and empowerment of the wider business. Serving as a data architect for Monzo's Borrowing data, contributing to the design and scalability of data models that measure the performance of our product suite. Develop robust data models downstream of backend services, primarily in BigQuery, to support internal reporting, machine learning, large language models, as well as financial and regulatory use cases. Be a key voice in shaping and maintaining best practices for our Data Warehouse, including source data payload design, logical data modelling, implementation, metadata, and testing standards. Collaboratively set standards and work with data across Monzo, fostering knowledge sharing and continuously improving data practices. Contribute to prioritising data governance issues, ensuring a comprehensive approach to data integrity and compliance. Being a key technical leader who's able to champion central platform initiatives that aim to elevate the data standards across Borrowing and beyond. We'd love to hear from you : You have a strong passion for data modelling, ETL projects, and Big Data. You enjoy working with data streams from various services, such as financial, transactional, and operational systems. SQL and data modelling are second nature to you, and you are comfortable with general Data Warehousing concepts. You are committed to continuous improvement, proactively identifying opportunities and addressing challenges in your work and the work of others. You have experience building robust and reliable data sets that require a high level of control. You enjoy working with cross functional fast moving teams and are passionate about serving our customers. You are able to think strategically about credit products and how our underlying data models will unlock more insights for our team and more value for our customers. You are excited about enabling other data scientists, analytics engineers and credit analysts by sharing your expertise on data architecture. You have the ability to shape big, ambiguous data domains and get the required buy-in from key leaders across the business. You are able to shape and manage the technical roadmap of an entire domain and execute against the project plan's deliverables. You are leading through the contributions of others by effectively leveraging the multiplier effect to create exponential value across Borrowing and Analytics Engineering. Excel in cross-functional stakeholder communication (back-end engineers, product managers, and credit analysts), while also effectively engaging with senior technical leaders. The interview process: Our interview process involves 4 main stages: Technical task 3 x 1 hours sessions (final interview) Our average process takes around 3-4 weeks but we will always work around your availability. This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London). We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team. Learning budget of £1,000 a year for books, training courses and conferences. And much more, see our full list of benefits here

Our Borrowing Analytics Engineering Team: Our Mission in Borrowing is to enable people's financial goals through better borrowing. Our customers look to borrow money to enable them to achieve something in their lives - whether that's making a big life event affordable, buying something they need now without affecting their monthly budget, or getting by until payday. And we're looking to shape this mission by building products that our customers love, whilst scaling those top revenue lines across the business safely. We're looking for a Lead Analytics Engineer within our borrowing team to help build world class service for the bank of the future. You will play a critical role in overseeing our foundational data platforms, identifying and driving opportunities to enhance our current capabilities. Your expertise will be pivotal in allowing us to scale into new global markets, build new products and shape the future of how we serve our customers. We have a strong culture of data-driven decision making across the whole company. And we're great believers in powerful, real-time analytics and empowerment of the wider business. Serving as a data architect for Monzo's Borrowing data, contributing to the design and scalability of data models that measure the performance of our product suite. Develop robust data models downstream of backend services, primarily in BigQuery, to support internal reporting, machine learning, large language models, as well as financial and regulatory use cases. Be a key voice in shaping and maintaining best practices for our Data Warehouse, including source data payload design, logical data modelling, implementation, metadata, and testing standards. Collaboratively set standards and work with data across Monzo, fostering knowledge sharing and continuously improving data practices. Contribute to prioritising data governance issues, ensuring a comprehensive approach to data integrity and compliance. Being a key technical leader who's able to champion central platform initiatives that aim to elevate the data standards across Borrowing and beyond. We'd love to hear from you : You have a strong passion for data modelling, ETL projects, and Big Data. You enjoy working with data streams from various services, such as financial, transactional, and operational systems. SQL and data modelling are second nature to you, and you are comfortable with general Data Warehousing concepts. You are committed to continuous improvement, proactively identifying opportunities and addressing challenges in your work and the work of others. You have experience building robust and reliable data sets that require a high level of control. You enjoy working with cross functional fast moving teams and are passionate about serving our customers. You are able to think strategically about credit products and how our underlying data models will unlock more insights for our team and more value for our customers. You are excited about enabling other data scientists, analytics engineers and credit analysts by sharing your expertise on data architecture. You have the ability to shape big, ambiguous data domains and get the required buy-in from key leaders across the business. You are able to shape and manage the technical roadmap of an entire domain and execute against the project plan's deliverables. You are leading through the contributions of others by effectively leveraging the multiplier effect to create exponential value across Borrowing and Analytics Engineering. Excel in cross-functional stakeholder communication (back-end engineers, product managers, and credit analysts), while also effectively engaging with senior technical leaders. The interview process: Our interview process involves 4 main stages: Technical task 3 x 1 hours sessions (final interview) Our average process takes around 3-4 weeks but we will always work around your availability. This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London). We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team. Learning budget of £1,000 a year for books, training courses and conferences. And much more, see our full list of benefits here