37 jobs found

We're on a mission to make money work for everyone. We're waving goodbye to the complicated and confusing ways of traditional banking. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We're not about selling products - we want to solve problems and change lives through Monzo Our Borrowing Analytics Engineering Team Our mission in Borrowing is to help people achieve their financial goals through better borrowing. Our customers borrow money 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. We're shaping this mission by building products our customers love, while safely scaling some of Monzo's biggest revenue lines. Borrowing is one of Monzo's most complex and fastest-growing domains. We operate 12+ products across multiple geographies, underpinned by 1,700+ data models and an analytics engineering team that's scaling to match. We're in the middle of a major data architecture transformation, expanding into new markets, and building the next generation of data infrastructure to support it all. We're looking for a Staff Analytics Engineer to help shape how Borrowing builds and uses data at scale. Reporting to the Borrowing Data Director, you'll work across product, credit, engineering, Data Platform, and analytics engineering teams to turn complex technical problems into clearer systems, stronger data products, and better business decisions. Architecting Borrowing's data layer at scale. Partnering across Analytics Engineering, Product, Engineering, Credit, and Data Platform to shape how 1,700+ models across 12+ products are structured, connected, and evolved. You'll set shared patterns that help teams build trusted, consistent, and scalable data products across Borrowing. Designing and governing data products. Moving us beyond ad-hoc tables toward well-defined, contractual data assets with clear ownership, SLAs, documentation, and interfaces. You'll work with teams across Borrowing and Data Platform to define what makes a Borrowing dataset "production-grade" and consumable by analytics, ML, decisioning, and regulatory teams. Building feature stores and reusable analytical assets. Identifying cross-product signals (credit behaviour, repayment patterns, affordability, risk indicators) that should be modelled once, tested rigorously, and consumed by many. You'll design the layer that turns raw product data into curated, versioned features that power models, dashboards, and decisions. Scaling our analytics engineering infrastructure. Shaping the tooling, patterns, and developer experience that make an 80+ person credit and data organisation more productive. This means influencing our data architecture and ways of working across data and credit disciplines, while partnering with the central Data Platform team to ensure Borrowing's needs are reflected in ingestion, streaming, and schema contract design. Driving cross-product data consistency. As we expand across geographies and product lines, ensuring our data models are coherent and comparable. You'll work with AE leads and domain experts to define shared conventions and abstractions that allow us to reason about Borrowing as a whole, not just product-by-product. Being a senior technical partner for Borrowing's data estate. Partnering with backend engineers on source data payload design, with product managers on measurement strategy, with credit teams on decisioning data, and with senior leadership on what's possible and what's next. Leading through influence and leverage. You won't manage people directly, but you'll shape how an entire domain builds data. You'll multiply the impact of AEs across Borrowing by setting the right patterns, unblocking architectural decisions, and raising the bar on what good looks like. You think in systems, not just queries. You've designed data architectures that span multiple products or domains, and you know how to keep them coherent as they scale. You can take ambiguous problems and turn them into a clear technical direction, delivery sequence, and set of trade-offs. You've built data products, not just data models. You understand the difference between a table that exists and a data asset that's governed, documented, versioned, discoverable, and trusted. You've defined SLAs, contracts, interfaces, or ownership models for data consumers, and you're excited to do this at scale. You have deep fluency with analytics engineering systems and infrastructure. dbt at scale, BigQuery or equivalent, CI/CD for data, testing frameworks, and orchestration. You don't just use these tools, you shape how teams use them. You've hit the scaling limits and know what to do about them. You can design reusable feature layers. You've designed, contributed to, or have a clear vision for reusable feature layers that serve multiple consumers, including ML pipelines, dashboards, decisioning engines, and regulatory reporting. You understand the trade-offs between freshness, cost, granularity, correctness, and ease of use. You're comfortable at the platform boundary. You can have a productive conversation with a Data Platform engineer about ingestion patterns, streaming vs. batch trade-offs, schema evolution, and infrastructure costs. You don't need to build the platform, but you need to shape what it delivers. You connect technical choices to business outcomes. You care about whether data models, feature layers, and platform patterns actually improve decisions. You understand how product, credit, engineering, and operational teams use data, and you use that context to align people around better technical choices. You lead through others. You create leverage not by writing more SQL, but by setting patterns, reviewing designs, unblocking teams, and raising the standard. You're energised by making 30+ people more effective, not by being the single expert. You communicate across altitudes. You can whiteboard a data architecture with a back-end engineer in the morning and present a strategic data roadmap to a director in the afternoon. You adapt your message to your audience without losing precision. You care about credit products. You're excited, or curious, about the complexity of lending, including risk, affordability, regulatory constraints, and multi-product dynamics. You see it as a fascinating data domain, not just a business vertical. Our typical process is structured as: 3 x 1 hours sessions (final interview) Our average process takes around 3-4 weeks but we will always work around your availability. What's in it for you: We can help you relocate to the UK We can sponsor visas 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 Equal opportunities for everyone Diversity and inclusion are a priority for us and we're making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we're embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog , 2026 Diversity and Inclusion Report and 2025 Gender Pay Gap Report. We're an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status. If you have a preferred name, please use it to apply. We don't need full or birth names at application stage

We're on a mission to make money work for everyone. We're waving goodbye to the complicated and confusing ways of traditional banking. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We're not about selling products - we want to solve problems and change lives through Monzo Our Borrowing Analytics Engineering Team Our mission in Borrowing is to help people achieve their financial goals through better borrowing. Our customers borrow money 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. We're shaping this mission by building products our customers love, while safely scaling some of Monzo's biggest revenue lines. Borrowing is one of Monzo's most complex and fastest-growing domains. We operate 12+ products across multiple geographies, underpinned by 1,700+ data models and an analytics engineering team that's scaling to match. We're in the middle of a major data architecture transformation, expanding into new markets, and building the next generation of data infrastructure to support it all. We're looking for a Staff Analytics Engineer to help shape how Borrowing builds and uses data at scale. Reporting to the Borrowing Data Director, you'll work across product, credit, engineering, Data Platform, and analytics engineering teams to turn complex technical problems into clearer systems, stronger data products, and better business decisions. Architecting Borrowing's data layer at scale. Partnering across Analytics Engineering, Product, Engineering, Credit, and Data Platform to shape how 1,700+ models across 12+ products are structured, connected, and evolved. You'll set shared patterns that help teams build trusted, consistent, and scalable data products across Borrowing. Designing and governing data products. Moving us beyond ad-hoc tables toward well-defined, contractual data assets with clear ownership, SLAs, documentation, and interfaces. You'll work with teams across Borrowing and Data Platform to define what makes a Borrowing dataset "production-grade" and consumable by analytics, ML, decisioning, and regulatory teams. Building feature stores and reusable analytical assets. Identifying cross-product signals (credit behaviour, repayment patterns, affordability, risk indicators) that should be modelled once, tested rigorously, and consumed by many. You'll design the layer that turns raw product data into curated, versioned features that power models, dashboards, and decisions. Scaling our analytics engineering infrastructure. Shaping the tooling, patterns, and developer experience that make an 80+ person credit and data organisation more productive. This means influencing our data architecture and ways of working across data and credit disciplines, while partnering with the central Data Platform team to ensure Borrowing's needs are reflected in ingestion, streaming, and schema contract design. Driving cross-product data consistency. As we expand across geographies and product lines, ensuring our data models are coherent and comparable. You'll work with AE leads and domain experts to define shared conventions and abstractions that allow us to reason about Borrowing as a whole, not just product-by-product. Being a senior technical partner for Borrowing's data estate. Partnering with backend engineers on source data payload design, with product managers on measurement strategy, with credit teams on decisioning data, and with senior leadership on what's possible and what's next. Leading through influence and leverage. You won't manage people directly, but you'll shape how an entire domain builds data. You'll multiply the impact of AEs across Borrowing by setting the right patterns, unblocking architectural decisions, and raising the bar on what good looks like. You think in systems, not just queries. You've designed data architectures that span multiple products or domains, and you know how to keep them coherent as they scale. You can take ambiguous problems and turn them into a clear technical direction, delivery sequence, and set of trade-offs. You've built data products, not just data models. You understand the difference between a table that exists and a data asset that's governed, documented, versioned, discoverable, and trusted. You've defined SLAs, contracts, interfaces, or ownership models for data consumers, and you're excited to do this at scale. You have deep fluency with analytics engineering systems and infrastructure. dbt at scale, BigQuery or equivalent, CI/CD for data, testing frameworks, and orchestration. You don't just use these tools, you shape how teams use them. You've hit the scaling limits and know what to do about them. You can design reusable feature layers. You've designed, contributed to, or have a clear vision for reusable feature layers that serve multiple consumers, including ML pipelines, dashboards, decisioning engines, and regulatory reporting. You understand the trade-offs between freshness, cost, granularity, correctness, and ease of use. You're comfortable at the platform boundary. You can have a productive conversation with a Data Platform engineer about ingestion patterns, streaming vs. batch trade-offs, schema evolution, and infrastructure costs. You don't need to build the platform, but you need to shape what it delivers. You connect technical choices to business outcomes. You care about whether data models, feature layers, and platform patterns actually improve decisions. You understand how product, credit, engineering, and operational teams use data, and you use that context to align people around better technical choices. You lead through others. You create leverage not by writing more SQL, but by setting patterns, reviewing designs, unblocking teams, and raising the standard. You're energised by making 30+ people more effective, not by being the single expert. You communicate across altitudes. You can whiteboard a data architecture with a back-end engineer in the morning and present a strategic data roadmap to a director in the afternoon. You adapt your message to your audience without losing precision. You care about credit products. You're excited, or curious, about the complexity of lending, including risk, affordability, regulatory constraints, and multi-product dynamics. You see it as a fascinating data domain, not just a business vertical. Our typical process is structured as: 3 x 1 hours sessions (final interview) Our average process takes around 3-4 weeks but we will always work around your availability. What's in it for you: We can help you relocate to the UK We can sponsor visas 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 Equal opportunities for everyone Diversity and inclusion are a priority for us and we're making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we're embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog , 2026 Diversity and Inclusion Report and 2025 Gender Pay Gap Report. We're an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status. If you have a preferred name, please use it to apply. We don't need full or birth names at application stage

We're on a mission to make migration easy. We started building Marshmallow in 2017. Since then, we've grown from 3 to 700+ people, gained unicorn status, raised £140M over three funding rounds, turned profitable, insured millions of drivers and lent millions in car loans. But we're only just getting started. Our goal is to become one of the largest financial services providers in the world. Over the next 10 years we'll grow exponentially, not only by scaling our existing products, but also by building new ones. To achieve our goals we need incredibly ambitious, commercially driven people who never settle for 'good enough'. Marshmallowers are hungry for autonomy and ownership, and would rather improve than coast. Everyone raises standards and has an impact, with a focus on collective success over self-interest. We've created an environment where curious, tenacious people win and grow together. If that sounds motivating, this could be the place for you. London (hybrid, 3 days in office) Data Science at Marshmallow Our Data Science team partners across the business to turn data into better decisions, smarter products, and simpler customer journeys. We work closely with Product, Engineering, and Operations to build and ship models and AI systems that are reliable in production and deliver measurable impact. Within Data Science, this role sits in Claims, supporting the function and the broader ambition to automate more of the claims journey. Claims is one of Marshmallow's most important customer touchpoints, and we're looking for a Principal Data Scientist who can provide technical leadership across traditional ML and Generative AI, bring system level thinking to how we scale decisioning, and confidently challenge proposals to ensure we build robust, sustainable solutions. What you'll be doing Provide technical leadership for data science across Claims Fraud, shaping the approach to risk decisioning and fraud detection in partnership with Product and Engineering Design, build and iterate on production ML and Generative AI/LLM systems that support claims validation and automation Collaborate closely with other Claims data scientists to bring system level thinking to how models, data and workflows fit together, identifying architectural improvements needed to scale decisioning and reduce time to production Be vocal about the platform and tooling investments needed (monitoring, feedback loops, QA) to achieve AI driven end to end claims automation Advocate for robust, scalable, and strategically aligned technical solutions in cross functional discussions, ensuring current systems and infrastructure contribute to the multi year vision for automated claims handling Set a high bar for statistical rigour, experimentation and measurement, helping improve how Claims performance and uncertainty are understood and communicated to senior stakeholders Who You Are You think in systems: you can connect the dots between data science, engineering, and product to shape scalable solutions that build on each other over time. You're confident in challenging assumptions and pushing for the right approach, using strong communication skills to influence stakeholders across seniority levels and disciplines with clear, pragmatic reasoning. You thrive in ambiguity and change, staying resilient and effective during transitions while bringing structure, clarity, and momentum to complex problem spaces. You're motivated by real world impact, partnering closely with cross functional teams to drive meaningful automation and better customer outcomes across the claims journey. What You'll Bring Significant commercial experience delivering end to end Machine Learning solutions, from problem framing and experimentation through to production deployment and ongoing monitoring Hands on experience building and shipping Generative AI systems in production (not just prototypes), including evaluation, safety/quality considerations, and integration into customer or operational workflows Strong statistical and modelling foundation, with experience in risk based decisioning under uncertainty (e.g., fraud, credit, insurance, or other regulated domains) Proven ability to influence technical direction across Data Science and Engineering, including shaping scalable model/service integration patterns and challenging proposals to drive robust, long term solutions Strong stakeholder management skills, with confidence communicating trade offs and pushing back constructively with Product and Engineering to ensure high quality outcomes Perks of the job Bonus scheme designed to reward high performance Private medical insurance with Vitality, mental health support with Oliva Personal learning budget and 2 dedicated L&D days a year Monthly flexible benefits budget to spend as you choose 25 days holiday plus bank holidays 4 weeks Work From Anywhere per year We are able to offer visa sponsorship for this position. Our process Initial call with a member from our Talent Team (30 mins) Past Experience interview with Hiring Manager (60 mins) Systems Design & Technical interview with a couple of the team (90 mins) Culture interview (60 mins) Diversity of thought We know the best ideas come from having different perspectives in the room - and we're committed to hiring fairly, regardless of background, identity or experience. If you see yourself in this role, we'd encourage you to apply.

Data Director, Workforce Systems & Service Performance Cardiff, London or Remote (UK); London We're waving goodbye to the complicated and confusing ways of traditional banking. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We're not about selling products - we want to solve problems and change lives through Monzo. Customer Operations at Monzo is at the heart of delivering fast, safe and high-quality support to millions of customers. As Monzo grows, the way we run operations is evolving. We're supporting more customers, more products, more markets, more regulatory expectations, and a growing mix of human and AI-powered service. This creates one of the most interesting operational systems challenges at Monzo: how do we forecast demand, plan supply, schedule work, route tasks, understand live performance, and make capacity decisions across an increasingly complex global operation? Workforce systems are central to this. They help determine how Monzo matches customer demand with human and AI capacity, how we protect service levels, how we make cost and capacity trade-offs, and how we keep support fast, safe and reliable as we scale. The next phase is about building the workforce systems that allow Monzo to keep scaling Customer Operations as we expand our products, global footprint and AI capabilities - supporting our mission to make money work for everyone. This role will lead that next phase. You'll sit at the intersection of Data, Product, Engineering, Operations and Finance. You'll shape the technology, data products and operating systems that help Monzo understand demand, plan capacity, schedule work, measure execution, assign tasks, and respond to live operational change. You'll work on capabilities that make workforce decisions more accurate, more automated, more explainable and more resilient as the business grows. You'll also build and develop the team and capability needed for this next stage - raising the bar for forecasting, measurement, operational data products and system-led workforce decisioning. You don't need to come from a traditional Workforce Management or contact centre background. We're looking for a senior data-product systems leader who can reason from first principles, build scalable operational systems, and lead through ambiguity across multiple disciplines. Key responsibilities Leading the strategy for Monzo's Workforce Systems across forecasting, capacity planning, scheduling, work status, task assignment and service performance. Building and developing a high-performing team across forecasting, measurement, analytics and operational data products, while helping shape the wider workforce systems roadmap with Product and Engineering. Building production grade data products that support live operational decisions - including forecasting, schedule fit, work status signals, capacity impact, throughput and service performance measures. Improving how we forecast and plan demand, including forecast accuracy, bias, uncertainty, feedback loops, and the impact of new products, new markets, AI agents and changing customer behaviour. Connecting forecasts, schedules and live execution so teams can understand how operational reality is changing and take action at the right time. Developing stronger system controls for capacity decisions, including forecast releases, demand changes, operational process changes, tooling launches and staffing decisions. Evolving how Forecast Change Requests and capacity impacting changes work, moving toward system supported decisioning, impact assessment and guardrails. Partnering deeply with Product and Engineering to define and build the workflows, metrics, controls and technical capabilities that help teams make better workforce decisions. Helping evolve task assignment and routing so work is allocated based on schedule, skill, capacity, prioritisation logic and live service needs. Raising the analytical and statistical bar across workforce planning and service performance, helping teams reason clearly about forecast error, AHT, workload, volatility, throughput, schedule adherence and customer outcomes. Transforming the operating model for the next stage of scale, helping teams move toward exception based operation, feedback loops and system led control. Working with senior leaders across Ops, Data, Product, Engineering and Finance to make trade offs between service quality, cost, capacity, risk and speed of execution. Required qualifications and experience You've led data products, forecasting systems, marketplace systems, logistics systems, operational platforms or live decision systems where data and models directly influenced how a business operated. You have strong first principles systems thinking and can break complex operational problems into clear components, feedback loops, controls and product opportunities. You have strong statistical judgement - you understand forecasting, uncertainty, bias, volatility, measurement quality, and when a metric is ready to support an operational decision. You're product minded: you think about users, workflows, incentives, adoption, decision points, and how tooling can make good decisions easier. You're credible with Engineering and can partner on architecture, reliability, system design, productisation, sequencing and trade offs. You've built, led or scaled teams working across data, product, engineering or operational systems. You're comfortable working in live operational environments, where decisions affect customers, cost, risk, regulation and service performance. You can lead through ambiguity and influence senior stakeholders across Product, Engineering, Data, Ops and Finance. You're a builder leader: you've created teams, systems, processes or capabilities that scale. You're excited by the challenge of building workforce systems for a future where human and AI capacity operate together. You're motivated by Monzo's mission to make money work for everyone, and by the role Operations plays in delivering fast, safe and high quality customer support as we grow. Desired background You may have worked in data science, data products, operational systems, forecasting, marketplace operations, logistics, planning systems, routing, service platforms, AI enabled operations, or another complex supply/demand environment. Experience in Workforce Management, customer operations, outsourcing, or contact centres would be useful, but it's not required. We care more about your ability to understand complex systems, build data products that power operational decisions, and lead across Data, Product, Engineering and Operations. The opportunity This is a senior technology and data leadership role focused on building the next generation of workforce systems at Monzo. The role sits at the intersection of Data Science, Product, Engineering and Operations. It needs someone who can bring statistical judgement, product thinking, technical credibility and people leadership together to shape systems used in live operational decision making. You'll help Monzo continue to scale Customer Operations as our product set, customer base, AI capabilities and global footprint grow. Benefits £120,000-£175,000 + Benefits. We'll help you relocate to the UK, if applicable. We can sponsor your visa. This role can be based in our London office, but we're open to distributed working within the UK, with occasional meetings in London. We offer flexible working hours and trust you to work enough hours to do your job well. £1,000 learning budget each year to use on books, training courses and conferences. We'll set you up to work from home; all employees are given MacBooks and remote workers get extra support for their home setup. Plus lots more - read our full list of benefits. Equal opportunity statement Equal opportunities for everyone. Diversity and inclusion are a priority for us and we're making sure we have lots of support for all of our people to grow at Monzo. We're an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, veteran, neurodiversity or disability status. If you have a preferred name, please use it to apply. We don't need full or birth names at application stage.

We're looking for a tech leader ready to take their career to new heights. Join the ranks of top talent at one of the world's most influential companies. As a Senior Principal Software Engineer at JPMorganChase within Infrastructure Platforms - Cloud Foundation Services, you provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead the strategic development behind new and existing products and technology portfolios, and remain at the forefront of industry trends, best practices, and technological advances. Job responsibilities Advises and leads on the strategy and development of multiple products, applications, and technologies across a portfolio Creates novel code solutions and drives the development of new production code capabilities across teams and functions Translates highly complex technical issues, trends, and approaches to leadership to drive the firm's innovation and enable leaders to make strategic, well-informed decisions about technology advancements Drives adoption and implementation of technical methods in specialized fields in line with the latest product development methodologies Creates durable, reusable software frameworks that are leveraged across teams and functions Influences across business, product, and technology teams and successfully manages senior stakeholder relationships Champions the firm's culture of diversity, opportunity, inclusion, and respect Sets and scales multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation (using enterprise-authorized tools within the work environment) to drive firmwide objectives (speed, scalability, reliability, and cost-to-serve), including portfolio-level standards for AI-orchestrated delivery workflows, release governance, automated test modernization, resilience engineering, and incident response acceleration; establishes guardrails for validation, security, resiliency, traceability, and reuse Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive cross-domain reuse and measurable capacity unlock outcomes across departments Required qualifications, capabilities, and skills Proven software engineering experience Practical experience delivering system design, application development, testing, and operational stability Expert in one or more programming language(s): Java, Go, Python, Rust, etc. Demonstrated prior experience with influencing across functions and teams and delivering value at scale Experience applying expertise and new methods to determine solutions for complex technology problems across various technical disciplines Extensive practical cloud native experience Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field Experience leading multi-organization adoption of agentic AI-enabled engineering operating models (using enterprise-authorized tools within the work environment), including defining governance (human-in-the-loop decisioning, quality gates), measurement frameworks, and secure handling of sensitive inputs/outputs across teams Deep understanding of responsible AI risk, controls, and resiliency/security expectations at scale, with demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies Preferred qualifications, capabilities, and skills Strong experience with cloud-native architecture, event-driven architecture, test-driven development Domain-level expertise in building continuous compliance systems at scale in financial services Expert-level understanding and experience with regulatory and industry standards relating to technology controls in financial services

Description This is seeking a Decisioning Architect to join their Personalisation Strategy and Decisioning team. This role involves embedding the customer contact strategy and optimizing the Pega Customer Decisioning Hub for personalized marketing. The company values hybrid working to balance office presence with home working, ensuring effective team collaboration while prioritizing personalized customer interactions. This position is offered as a 12-month Fixed Term Contract based in either Swindon or London.

We are looking for a 'Decisioning Architect' to join the Personalisation Strategy and Decisioning team within the Group Customer and Communications (GCC) function. We are on an exciting journey to transform our capability to deliver personalised 1:1 customer marketing. We are embarking on a strategy that will see us uplift the technology we use for marketing and transform how we use data to deliver personalised experiences for our customers. This role specifically sits within the 'Personalisation team', and you'll be working for our Decisioning and Contact Strategy Senior Manager. You will be responsible for embedding our overall customer contact strategy while ensuring the wider Personalisation and Customer marketing teams are creating and delivering personalised, relevant, and timely interactions, with our members at the heart. You will also optimise one of our key marketing technology platforms, the Pega Customer Decisioning Hub (CDH) platform, to achieve Society goals with the sophistication and complexity growing in line with the uplift in our data and tech capability. We are happy to consider flexible working approaches to help you perform at your best. The working hours (per week) for this role are between 31.5 and 35 hours. This is a 12-month Fixed Term Contract. At Nationwide, we offer hybrid working wherever possible. More rewarding relationships are supported through our hybrid approach, bringing colleagues together across our UK-wide estate, whilst also supporting generous access to home working. We value our time in the office to solve problems, to learn, and to feel connected. For this job, you'll spend at least two days per week, or if part-time, you'll spend 40% of your working time, based at either our Swindon or London office. If your application is successful, your hiring manager will provide further details on how this works. You can also find out more about our approach to hybrid working here. If we receive a high volume of relevant applications, we may close the advert earlier than the advertised date, so please apply as soon as you can.

As an Analytics Engineer, you'll own the data models and transformations that underpin credit decisioning, pricing, portfolio performance, and investor reporting for our UK and US businesses. You'll work closely with analysts, product teams, backend engineers, and business stakeholders to improve how data is structured, transformed, and consumed across the company. The role is fundamentally about building a strong analytical foundation: making it easier for teams to move from question to insight quickly, while maintaining high standards around data quality, scalability, and maintainability. You'll operate with a high degree of ownership, helping shape the modelling layer, improving how analysts work with data, and ensuring our warehouse remains a strategic asset for the business. What you'll be doing Owning and improving the data models that support lending decisions, pricing, portfolio analysis, and investor reporting. Driving the development of our dbt models and transformation layer, working with analysts and stakeholders to improve the speed and quality of insight generation. Helping define good modelling patterns, architecture, and implementation standards across the analytics engineering layer. Supporting and mentoring analysts at different technical levels, helping them build stronger engineering habits and become more effective with data. Acting as a bridge between analysts, backend engineers, product teams, and the data platform team to make sure data is generated, modelled, and used effectively. Leading triage and resolution of issues that affect the analytics pipeline or reduce trust in downstream datasets. Identifying opportunities to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time. Our modern data stack You'll work with a modern analytics stack centred around Snowflake, dbt, and Fivetran. What we're looking for We're looking for someone with strong analytics engineering fundamentals and the ability to apply them pragmatically in a fast moving environment. More specifically, we're looking for: Strong data modelling skills and a good understanding of how analytical datasets should be structured for reliability and usability. Strong experience with ELT pipelines and transformation at scale, ideally using dbt. Experience with Snowflake or another modern cloud data warehouse. Good judgement in balancing longer term platform improvements with day to day business needs. The ability to spot inefficiencies in existing data workflows and improve them independently. A collaborative working style and clear communication across technical and non-technical stakeholders. Comfort using AI tools effectively to move faster, improve quality, and strengthen day to day analytical and engineering workflows. An interest in helping analysts raise their technical bar through support, mentoring, and better shared patterns. Life at Lendable Winning team: the opportunity to scale up one of the world's most successful fintech companies Flexible working: flexible approach tailored to each role. Hybrid roles require three days in office weekly; fully remote roles include regular opportunities for in person connection through socials and off sites Socials & connection: opportunities and events to come together, socialise, and get to know each other beyond the office walls Health coverage: support for your physical and mental wellbeing, including private health cover Retirement & savings: long term financial wellbeing through retirement savings plans Employee referral programme: earn a competitive bonus when you refer successful new team members Office meals & snacks: enjoy a fully stocked kitchen, plus complimentary lunches prepared by in house chefs on in office days at select locations Sustainable commuting: cycle to work and electric vehicle salary sacrifice schemes available in select locations Please note: The availability and details of specific benefits vary by location and role. For more information, please speak to your Talent Partner.

About the Business LexisNexis Risk Solutions provides customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. We use the power of data and advanced analytics to help our customers make better, timelier decisions. By bringing clarity to information, we ultimately help make communities safer, commerce more transparent, business decisions easier and processes more efficient. You can learn more about LexisNexis Risk solutions at About the role Build and deploy ML powered services, tools, and full stack applications supporting fraud and identity analytics. Work across backend services, model serving pipelines, and user interfaces. Key Responsibilities Develop ML inference APIs, microservices, and data/feature pipelines. Build full stack tools to support model evaluation and transparency. Integrate ML models into real time production systems. Implement automated training, monitoring, and evaluation workflows. Use and contribute to AI assisted development tools. Own DevOps and security standards for assigned services. Collaborate with data scientists, architects, and QA. Required Experience 4+ years software engineering (backend, full stack, or ML). Strong Python and Java. Snowflake or similar data platform experience. Familiarity with ML model serving and feature engineering. Strong ownership and independent execution. Working knowledge of DevOps and secure engineering. Preferred Experience LLMs, embeddings, or vector databases. Behavioural, graph, or anomaly detection models. dbt, Snowpark, or Snowflake ML. Benefits Generous holiday allowance with the option to buy additional days. Health screening, eye care vouchers and private medical benefits. Wellbeing programs. Life assurance. Access to a competitive contributory pension scheme. Save As You Earn share option scheme. Travel Season ticket loan. Electric Vehicle Scheme. Optional Dental Insurance. Maternity, paternity and shared parental leave. Employee Assistance Programme. Access to emergency care for both the elderly and children. RECARES days, giving you time to support the charities and causes that matter to you. Access to employee resource groups with dedicated time to volunteer. Access to extensive learning and development resources. Employee discounts scheme via Perks at Work. Legal and EEO Statements We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights. At LexisNexis Risk Solutions, our businesses span multiple industries providing customers with innovative technologies, information based analytics, decisioning tools and data management services that provide market specific solutions. Approximately 11,100 employees in offices throughout the world support our brands by serving customers in more than 180 countries. LexisNexis Risk Solutions is part of RELX, a global provider of information and analytics for professional and business customers across industries. For more information, please visit and .

Sr Generative AI Engineer Location: London About The Role Dataiku is the platform for AI success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack-empowering organizations to run AI across multi-vendor environments with centralized governance. The world's leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. As a Sr Generative AI Engineer on the ED&A team, you will build the agentic AI systems that change how Dataiku runs internally. The role is hands on and end to end, working close to the business, turning real problems into working software, and seeing your solutions through from first conversation to production. How You'll Make an Impact Agentic AI Solution Development & Integration Design end to end AI solutions on Dataiku's platform, leveraging Dataiku Agent Hub, Prompt Studio, LLM Mesh, and Knowledge Banks (Vector Stores), or Python based frameworks where needed. Build and orchestrate multi agent systems using Dataiku's Visual Agents (simple and structured), as well as code based frameworks (LangGraph, CrewAI, Claude Agent SDK, OpenAI Agents SDK) as appropriate. Integrate and optimize LLM APIs across providers (OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure, open source models via Dataiku's LLM Mesh), applying model routing strategies to balance cost, latency, and quality. Implement Retrieval Augmented Generation (RAG) pipelines, including agentic RAG and GraphRAG, using Dataiku's Knowledge Banks with reranking, dynamic filtering, and document extraction capabilities. Stakeholder Engagement & Delivery Work primarily with the "Revenue" organisation-Sales, BDR, Customer Success, Solutions Engineering, Professional Services, Sales Operations and Marketing (approximately 75% of the role)-and apply proven solutions and approaches more broadly across the organisation (approximately 25%). Engage stakeholders to gather business requirements, then identify the underlying user pain those requirements represent, and design solutions that address both the stated need and the deeper problem. Own projects end to end, from requirements intake and solution design through to build, deployment, and handover. Agent & Tool Development Develop autonomous and semi autonomous AI agents, using Dataiku's Agent Builder, custom Python based architectures (LangGraph, CrewAI, Claude Agent SDK, etc.), or a combination of both. Exercise judgment on when to leverage platform capabilities and when to build custom solutions. Design and build Agent Tools beyond documented examples, including custom API integrations, data retrieval modules, decisioning logic, and automated workflows, pushing past out of the box patterns to deliver solutions tailored to specific business problems. Build, publish, and consume MCP (Model Context Protocol) servers to enable agent to tool integration across systems, including designing custom MCP servers where needed. Develop evaluation and monitoring approaches for agent systems, combining Dataiku's built in capabilities with custom instrumentation to measure reliability, accuracy, cost, and business impact in production. AI Governance & Evaluation Design and maintain evaluation frameworks (evals) for LLM based systems, measuring accuracy, latency, cost, and reliability in production. Adhere to data governance, security, and regulatory compliance requirements (EU AI Act awareness, responsible AI practices) for all AI solutions. Leverage Dataiku's Cost Guard and Quality Guard features to manage LLM spend, enforce usage policies, and maintain output quality standards. Work closely with analytics and data engineering teams to maintain metadata on reference datasets for LLM consumption. Web Application Development Create front end user interfaces for AI applications using HTML, CSS, and JavaScript, within Dataiku's webapps framework, Dataiku Answers for chat based interfaces, or standalone applications built with Vue.js and Node.js. Collaborate on UX design, ensuring internal stakeholders find AI solutions intuitive and responsive. Continuous Learning Provide product feedback to the development team to improve the platform. Stay current with the rapidly evolving AI engineering landscape, agent frameworks, model capabilities, evaluation practices, governance requirements, and tools like MCP and A2A protocols. What You'll Need to Be Successful Technical Proficiency Strong Python skills (including familiarity with typical data science and AI engineering libraries). Hands on experience building agentic AI systems, multi agent orchestration, tool chaining, autonomous decision making, and production deployment of AI agents. Experience with modern agent orchestration frameworks (LangGraph, CrewAI, Claude Agent SDK, OpenAI Agents SDK, or similar); familiarity with LangChain is relevant but not sufficient on its own. Understanding of RAG architectures (vector databases, embedding strategies, agentic RAG, GraphRAG) and when to apply each approach. Familiarity with MCP (Model Context Protocol) for agent to tool integration, or demonstrated ability to quickly adopt new integration standards. Experience with structured outputs, function/tool calling, and prompt engineering across multiple LLM providers. Web development fundamentals (HTML, CSS, JavaScript); experience with Vue.js and Node.js preferred. Exposure to AI evaluation practices, building evals, monitoring model/agent performance in production, and iterating based on metrics. Comfort with AI assisted development tools (GitHub Copilot, Cursor, Claude Code, or similar). Familiarity with Dataiku a bonus. Educational & Professional Background Bachelor's or Master's in Computer Science, Data Science, Engineering, or a related field; equivalent experience also considered. Demonstrated ability to integrate multiple technologies, optimize workflows, and deliver user friendly AI solutions in a production setting. Soft Skills Strong communication and presentation skills, capable of collaborating effectively with both technical and non technical stakeholders. Problem solving mindset with a passion for innovation and delivering measurable business value. Openness to learning new tools (e.g., Dataiku) and adapting to a rapidly evolving AI landscape. Equal Opportunity Employer Statement At Dataiku, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other protected characteristic in the locations where we operate. If you need assistance or an accommodation, please contact us at reasonable .

Lead Cloud Operations Engineer - (Cheltenham/Hybrid) About Finova Finova is the UK's largest mortgage and savings technology provider, powering one in every five mortgages across the country. Our agile, cloud-native solutions help over 60 banks, building societies, specialist lenders and equity release providers - plus a network of 2,400+ brokers - stay ahead of the market. We offer a flexible, proven suite of software that covers the full customer journey - from mortgage and savings origination to servicing and CRM. Backed by an open architecture and a team with deep industry expertise, our platform is built to scale. Today, we process over £50 billion in loans each year, manage nearly £50 billion in savings, and support the digital servicing of more than 650,000 UK borrower accounts. For Lenders Finova offers a flexible, modular technology suite designed to help lenders move faster, scale efficiently, and deliver standout digital experiences. You can run your entire mortgage and savings business on Finova - or just use the modules you need, tailored by our team or configured in-house through our low code platform. Our solutions include: Lending - end to end mortgage and specialist lending software built for speed, flexibility, and scale. Decisioning - powerful tools for smarter, more personalised lending decisions. Servicing - intuitive workflows and automation to simplify day to day account management and customer servicing. Savings - configurable onboarding and customer engagement tools across all savings products. Intermediary Manager - broker relationship and compliance management, powered by real time external data. Broker ID - fast, automated broker verification and compliance tracking using KYB, KYC, and live monitoring from public data sources. Lenders use Finova to launch products faster, process applications up to 50% more efficiently, and reduce operational costs - all while staying fully compliant in a fast moving market. About the Role As a Lead Cloud Operations Engineer, you will take a leading role in the availability, security, resilience, and performance of the Apprivo cloud platform. The role remains firmly hands on and operational, with additional responsibility for technical leadership, prioritisation, and operational readiness across the Cloud Operations function. Reporting to the Director of Cloud Operations, you will operate as a senior technical practitioner and escalation point, leading by example in day to day BAU operations and executing higher risk infrastructure changes. You will be crucial in maintaining high quality operational support while accelerating continual improvements in resilience, automation, monitoring, incident management maturity, and security posture within the contract timeframe. This role suits an experienced engineer who enjoys rapidly operating and improving complex SaaS platforms, providing hands on coaching, and collaborating closely with development, QA, security, and database teams to deliver critical services to regulated clients. About you You are an experienced, hands on Cloud Operations Engineer with a strong bias toward reliability, security, and operational discipline, combined with the ability to provide immediate technical leadership and drive results. You bring: Extensive experience in Cloud Operations, with deep hands on knowledge managing Azure hosted production environments, including Azure App Services, Application Gateways, and a strong understanding of Azure Networking components (VNets, Load Balancers, NSGs, routing). Strong technical competency in core infrastructure, including Windows Server administration, operational Microsoft SQL Server support (not a DBA role), and solid networking and load balancing fundamentals. Extensive experience executing and supporting CI/CD pipelines, including troubleshooting failed deployments and infrastructure automation issues. Strong monitoring and observability experience, using tools such as Datadog, Azure Monitor, Azure AppInsights, or equivalent, to proactively identify and resolve issues. A disciplined, process driven approach to change management, security, access control, and operational governance in regulated environments. What will you be doing Lead the operation of Apprivo Azure production and non production environments, with deep hands on ownership of Azure App Services, Azure Networking, storage, and compute. Drive immediate technical stabilization efforts, focusing on addressing root causes of recurrent platform defects, legacy configurations, and environmental vulnerabilities to secure a foundation for long term operational resilience. Act as a senior escalation point for platform and application issues, performing second and third line triage and coordinating incident resolution across teams. Execute and oversee higher risk infrastructure and platform changes, ensuring strong adherence to change management, security, and release controls. Support delivery teams with complex automated deployments and configuration changes, diagnosing and resolving failed or degraded releases. Provide operational support for Microsoft SQL Server alongside the DBA team, including service health checks, job monitoring, backup verification, basic performance triage, and supporting application teams during database related incidents. Work closely with DBA and development teams where deeper database design, query optimisation, schema changes, or platform tuning are required. Own and continuously improve monitoring and alerting standards, ensuring high signal to noise visibility of platform health and early detection of service impacting issues. Lead performance and capacity triage activities, identifying trends and bottlenecks before they affect service availability. Manage, participate in, and provide senior cover for, the out of hours on call rota, responding to P1/P2 incidents and supporting scheduled out of hours deployments. Lead and support resilience and disaster recovery activities, including failover testing, game days, and validation of runbooks and operational readiness. Assess, prioritise, and remediate vulnerability findings, working from automated security tooling, configuration reviews, and third party penetration test outputs. Lead incident post mortems, providing technical insight and ensuring agreed preventative actions are implemented. Assist with audit and compliance activities, gathering and validating operational evidence for ISO, regulatory, and client assurance exercises. Provide day to day technical leadership and guidance to Cloud Operations Engineers, helping prioritise work, coaching engineers, and improving runbooks, documentation, and operational standards. Establish and execute a structured skills transfer program, mentoring Cloud Operations Engineers on advanced Azure troubleshooting, security review processes, and high risk change execution, ensuring knowledge retention and increased team autonomy. Act as a reliable senior technical point of contact for internal and external stakeholders, providing clear, confident updates during incidents, changes, and BAU activities. What We Offer Hybrid working At Finova, we believe the best outcomes come from working together - and having the flexibility to work in a way that suits both our people and our business. We operate a hybrid working model, with most teams spending around three days a week in the office and with our customers. This time together helps us stay connected, collaborate more effectively, and solve complex challenges as a team. We also know that flexibility matters. Our approach is designed to support a healthy balance, combining in person collaboration with the freedom to work remotely where it makes sense. Holiday 25 days holiday plus bank holidays, bank holiday trading and holiday purchase options, the opportunity to work from anywhere in the world for up to 4 weeks per year. Looking After You Life Assurance, Group Income Protection, Private Medical Insurance, a pension scheme via Salary Exchange, an Employee Assistance Programme, and access to a Virtual GP. Family Friendly Policies Enhanced maternity and paternity pay, as well as paid time off for fertility treatments and pregnancy loss. Extra Perks Cycle to Work Scheme, discounts on shops, restaurants, and gym memberships, free fresh fruit daily, and opportunities to join colleague networks and social groups. Giving Back One paid volunteering day annually and the Give As You Earn scheme to support your favourite charities. Equal Opportunity Statement We value diversity and are committed to creating an inclusive environment for all employees.

About the Role Banks and fintechs use Taktile to automate critical decisions - like credit and risk - in real time. We're a startup in the automated decisioning space - and the backend is where the hard problems live. We're looking for a Senior Backend Engineer to join our engineering team. In Team Atlas you'll focus building the data infrastructure that powers our feature computation platform. You'll own critical systems end-to-end on a small team where your decisions shape the product. What You'll Do Build and operate backend services in Python on AWS - Lambda functions, DynamoDB, Aurora, and event-driven pipelines that handle real production traffic. You'll leverage agentic AI tools as part of your daily workflow. Tackle hard backend problems - latency, reliability, and scale are everyday concerns. Own your systems end-to-end: from architecture and implementation to deployment, monitoring, and incident response. Make key architectural decisions - you'll have real authority over how things are built, not just what gets built. Raise the bar for the team through code reviews, mentoring, and improving our development tooling and processes. Work directly with Product and Design to shape what we build next. Requirements At least 5 years of professional software engineering experience, with a proven track record of leading complex projects in a senior capacity (2+ years). Deep expertise in Python and building backend systems on cloud platforms (we use AWS). Strong system design skills - you're comfortable making architectural trade-offs and defending them. Depth in at least one of these areas: data pipelines and storage, event-driven architectures, caching and performance, or serverless systems. You don't need all of them. Strong communication and collaboration skills, with the ability to align technical and non-technical stakeholders on a shared vision. The ability to work in a hybrid model from our Berlin HQ, the London office, or the Iasi hub. Please note that relocation assistance is not provided for this role. Ideal, But Not Required Apache Iceberg, AWS Athena, AWS Glue, or Apache Spark Streaming / real-time data pipelines (Kinesis) Multi-level caching strategies (Redis, DynamoDB, in-memory) Serverless at scale (Lambda, SAM, CloudFormation) Our Offer Work with colleagues that lift you up, challenge you, celebrate you and help you grow. We come from many different backgrounds, but what we have in common is the desire to operate at the very top of our fields. If you are similarly capable, caring, and driven, you'll find yourself at home here. Experience a truly flat hierarchy and communicate directly with founding team members. Having an opinion and voicing your ideas is not only welcome but encouraged, especially when they challenge the status quo. Learn from experienced mentors and achieve tremendous personal and professional growth. Get to know and leverage our network of leading tech investors and advisors around the globe. Receive a top-of-market equity and cash compensation package. Get access to a self-development budget you can use to e.g. attend conferences, buy books or take classes. Receive a new Apple MacBook Pro, as well as meaningful home office set up. Our Stance We're eager to meet talented and driven candidates regardless of whether they tick all the boxes. We're looking for someone who will add to our culture, not just fit within it. We strongly encourage individuals from groups traditionally underestimated and underrepresented in tech to apply. We seek to actively recognize and combat racism, sexism, ableism and ageism. We embrace and support all gender identities and expressions, and celebrate love in its many forms. We won't inquire about how you identify or if you've experienced discrimination, but if you want to tell your story, we are all ears. About Us Taktile helps financial institutions make smarter, safer decisions with the power of AI. Our software gives teams the tools to automate complex decisions like who to onboard, how to underwrite, or when to flag suspicious activity with full visibility and control. By combining AI with a rich ecosystem of financial data, Taktile enables companies to adapt their decision making in real time as markets, customer behavior, and risks evolve. Our mission is to build the world's leading platform for automated decision making in financial services, setting the standard for how AI is applied responsibly and effectively in this industry. We were founded by machine learning and data science experts with deep experience in financial services. Today, our team works across Berlin, London, and New York, bringing together engineers, entrepreneurs, and researchers from companies like Google, Amazon, and Meta, as well as fast growing startups and enterprise leaders. Backed by top investors including Y Combinator, Index Ventures, Balderton Capital, and Tiger Global, along with the founders of Looker, GitHub, Mulesoft, Datadog, and UiPath, we're building a world class organization across all functions and levels to power the next generation of AI driven decision making in financial services.

Next Ventures is seeking an experienced Lead Decisioning Architect to oversee the delivery of a key project based in the EU. This long-term role spans up to three years and involves owning the target-state decisioning architecture, including the design of the Next-Best-Action framework across the organization. The successful candidate will collaborate with various teams to ensure consistency and performance of decisioning strategies while acting as a primary authority for architectural governance. Strong problem-solving skills and strategic thinking are essential.

Job Role Data Management and Analytics-Data development/developers Experience (In Years) 9-12 Job Location London, United Kingdom Job Description EXL (NASDAQ: EXLS)is a global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world's leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 60,000 employees spanning six continents. For more information, visit . Location: London, United Kingdom (Hybrid) Employment Type: Permanent Summary of the role: We are seeking a highly experienced Earnix SME to lead the design, implementation and optimisation of Earnix pricing solutions within our Insurance business. You will provide technical leadership across pricing architecture, model deployment, system integration, and pricing transformation initiatives, working closely with actuarial, underwriting, data, and technology teams. The ideal candidate will bring deep expertise in Earnix development and enterprise implementation, alongside strong knowledge of P&C insurance pricing, rating, and underwriting processes. Experience with APIs, Python, cloud technologies, and large-scale pricing system integrations is essential. As part of your duties, you will be responsible for: Provide technical support for Earnix configuration, customization, and integration with enterprise pricing systems and workflows Collaborate with actuarial, data, and IT teams to design and implement architecture supporting pricing and rating processes Work with solution architects and system engineers to optimize end-to-end pricing lifecycle, including data ingestion, model deployment, and monitoring Develop, enhance, and maintain Earnix-based pricing models and decisioning systems Ensure performance, scalability, and reliability of Earnix solutions in production environments Support integration with upstream/downstream systems (e.g., policy admin systems, data warehouses, APIs) Participate in testing, validation, and deployment of pricing models Troubleshoot and resolve technical and functional issues in pricing applications Contribute to best practices, documentation, and governance for pricing systems and actuarial processes Qualifications and experience we consider to be essential for the role: Bachelor's or master's degree in computer science, Actuarial Science, Mathematics, Engineering, or related field 5+ years of experience in insurance technology or pricing systems development Prior experience in Earnix implementation projects is highly preferred Strong experience with platforms like Earnix (configuration, modeling, deployment) Proficiency in Python and data handling for large datasets Experience with APIs, system integration, and microservices architecture Knowledge of cloud platforms is a plus Knowledge of data pipelines, ETL processes, and data modeling Solid understanding of P&C insurance pricing and underwriting processes Exposure to actuarial modeling, rating algorithms, and risk segmentation Familiarity with regulatory and compliance considerations in insurance pricing Strong analytical and problem-solving skills Ability to work collaboratively in cross-functional teams Excellent communication and stakeholder management skills Detail-oriented with a focus on quality and accuracy As part of a leading global Data and AI company, you can look forward to: A competitive salary with a generous bonus, private healthcare, critical illness life assurance at 4 x your annual salary, income protection insurance, and a rewarding pension. EXL provides everyday financial well-being solutions, such as cash back cards, in which you can earn cashback while enjoying discounts, promotions, and offers from top retailers. We also offer a Cycle Scheme where you can save money on bikes and cycling accessories. At EXL, we are committed to providing our employees with the tools and resources they need to succeed and excel in their careers. We offer a wide range of professional and personal development opportunities. We also support a range of learning initiatives that allow our employees to build on their existing skills and knowledge. From online courses to seminars and workshops, our employees have the opportunity to enhance their skills and stay up to date with the latest trends and technologies. As an Equal Opportunity Employer, EXL is committed to diversity. Our company does not discriminate based on race, religion, colour, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, age, or disability status. EXL employees are eligible to purchase stock as part of our Employee Stock Purchase Plan (ESPP). At EXL, we offer a flexible hybrid working model that allows employees to live a balanced, healthy lifestyle while strengthening our culture of collaboration. To be considered for this role, you must already be eligible to work in the United Kingdom.

Senior kdb+ Developer - BestXWe are seeking an experienced Senior kdb+ Developer to join the BestX engineering team. In this role, you will design, build, and optimise high performance data platforms using kdb+, supporting BestX's multi asset analytics capabilities.The ideal candidate brings deep expertise in kdb+ tick architectures, large scale performance tuning, and works closely with quantitative and engineering teams to deliver robust, efficient, and maintainable solutions.Key ResponsibilitiesDesign and develop key components of BestX's multi asset analytics platform.Architect, build, and maintain kdb+ tick systems, with strong consideration for data organisation, schema design, and architectural trade offs.Develop and operate systems that process large scale, high frequency datasets, ensuring low latency, high throughput, and efficient memory utilisation.Analyse and optimise q queries, data models, and ingestion pipelines for both real time and historical workloads.Apply modern Agile development practices across cloud based, server side, and database driven systems.Build a strong understanding of Transaction Cost Analysis (TCA) and key regulatory benchmarks required for MiFID and MiFIR.Take full ownership of deliverables, driving work through from design to production.Establish and promote best practices, clean code standards, and sound design patterns.Act as a change agent, continuously improving engineering standards and ways of working.Champion Test Driven Development and "shift left" practices to support effective CI/CD pipelines.Core (Must Have) Skills and Experience5+ years of hands on kdb+ development experience.Strong expertise in kdb+/q and Python.Proficiency with modern data science toolchains, including Jupyter, pandas, NumPy, scikit learn, with applied machine learning experience.Solid understanding of parallel computing frameworks such as Slurm or equivalent technologies.Strong background in quantitative analysis, including mathematical modelling, statistics, regression, and probability theory.Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related STEM discipline from a top ranked university.Hands on experience with AWS and/or other modern cloud based infrastructure.Nice to Have SkillsDomain knowledge in FX, Fixed Income, Equities, or Equity Derivatives.Additional expertise with kdb+ in complex, production scale environments.Exposure to modern JavaScript build toolchains, including Node.js, npm, Rush, Yarn, Webpack, Babel, and Cypress.About State Street & BestXState Street is a global financial services leader, combining scale, resilience, and advanced technology to support institutional investors worldwide. Through investment servicing, trading, data, and analytics, we build mission critical platforms that operate at the heart of global financial markets.BestX, part of State Street's Global Markets and GlobalLink ecosystem, is the industry standard, multi asset Transaction Cost Analysis (TCA) platform. Built as a high performance analytics platform, BestX processes over one billion market data updates per day, delivering independent, venue agnostic insights across FX, fixed income, and equities.BestX has been recognised globally for its technology and impact, including:World's Best Provider of TCA Solutions - Euromoney Markets Awards 2025Best Transaction Cost Analysis Solution - WatersTechnology Asia Awards 2025World's Best New FX Product/Platform for BestXecutor - Euromoney 2025BestX and BestXecutor embed advanced analytics directly into trading workflows, spanning pre trade decisioning through post trade validation, helping clients improve execution quality and meet evolving regulatory requirements at scale.At State Street, you'll work on complex, high performance systems alongside leading engineers, quants, and product teams-shaping the future of execution analytics and global market infrastructure in an inclusive, supportive environmentAbout State StreetAcross the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you'll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.Discover more information on jobs at our CEO Statement

Position Type: Full time Type Of Hire: Experienced (relevant combo of work and education) Education Desired: Associate's Degree At FIS, our technology and our people are moving forward. We advance the way the world pays, banks and invests. We believe in building inclusive, diverse teams. Together, we innovate to help our colleagues, clients and communities succeed. If you're ready to grow your career and make an impact in fintech, we have one question: Are you FIS? About the role Are you ready to shape the future of AI within one of the world's most influential fintech companies? At FIS, we're hiring an experienced Engineer Principal, Artificial Intelligence / Machine Learning to define, lead, and execute our enterprise wide AI/ML vision. In this strategic and highly visible role, you will architect and drive cutting edge AI systems that power transformation across our global commercial organization. You'll lead the design and development of advanced machine learning algorithms, intelligent agents, and enterprise scale AI platforms-solving complex challenges unique to fintech. You will work closely with cross functional teams-including product managers, software engineers, data scientists, and business leaders-to build and embed AI solutions into FIS products, tools, and processes. You'll also shape how the entire commercial organization interacts with AI through modern architectures and next generation agentic systems. What you will be doing Providing strategic leadership and owning the AI/ML roadmap for the commercial organization. Leading and growing a high calibre team of Data Scientists and AI/ML engineers, fostering a culture of innovation, collaboration, and continuous learning. Designing, building, and deploying AI Agents at scale-from automated lead generation agents to intelligent pricing and decisioning systems. Developing advanced ML models and agentic systems to address complex challenges across fintech, including predictive analytics, optimization, personalization, and intelligent automation. Owning the strategy and architecture for how the entire commercial organization interacts with AI, including model governance, tooling, infrastructure, and integration frameworks. Collaborating with stakeholders across Sales, Product, Engineering, and Revenue Operations to embed AI capabilities into workflows, products, and commercial strategies. Driving innovation in Generative AI, Agentic AI, deep learning, and large scale ML deployment. Championing best practice in MLOps, cloud native development (Azure preferred), and scalable production deployment. Presenting AI program outcomes, strategic recommendations, and technical guidance to senior leadership and executive audiences. What you will need Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or related field (required). Master's or PhD in AI/ML, Computer Science, or related discipline (preferred). 8+ years of experience in AI/ML engineering, applied machine learning, or advanced analytics. Demonstrated experience leading technical AI teams and delivering enterprise scale AI/ML solutions. Deep expertise in machine learning algorithms, neural networks, large scale architectures, and modern AI frameworks. Hands on experience with Generative AI and Agentic AI (LLMs, foundation models, autonomous agents, large scale inference). Strong proficiency in Python and SQL; experience building production grade ML systems. Experience with Azure or another major cloud platform; familiarity with MLOps pipelines and deployment automation. Excellent communication skills and the ability to simplify complex technical concepts for business audiences. Ability to thrive in a fast paced, high impact environment with multiple stakeholders. Curiosity, proactive problem solving mindset, and passion for innovation. What we offer you Opportunities to innovate in fintech and shape the future of enterprise AI. Inclusive and diverse team atmosphere. Professional and personal development. Resources to contribute to your community. Competitive salary and benefits. FIS Global

Role Overview A backend engineering role building lending platforms that support credit decisioning, loan origination, and servicing. You'll work on systems that directly impact customer access to finance. Key Responsibilities Develop backend services for lending platforms Build scalable APIs and workflows Collaborate with product teams Improve system reliability Support integrations with third parties Required Experience Backend engineering experience Financial services or lending exposure API development skills Experience with transactional systems Cloud platform exposure Nice to Have Credit decisioning systems Event-driven architectures SaaS platform experience Why Join Customer-impacting technology End-to-end system ownership Strong growth sector