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Ripple is seeking a Staff Data Scientist to lead analytics across its product and business portfolio. This role involves defining the analytics vision, building frameworks and pioneering AI to enhance decision-making. The ideal candidate has over 8 years of experience in data science, technical leadership capabilities, and a strong background in quantitative analysis. Ripple fosters a collaborative and inclusive environment, offering competitive salaries and generous benefits.

At Ripple, we're building a world where value moves like information does today. It's big, it's bold, and we're already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs. If you're ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value. THE WORK: We're looking for a Staff Data Scientist to be the technical lead across Ripple's diverse product and business portfolio. You'll define the analytics vision, build the scientific frameworks the org uses to evaluate product and business performance, and use AI tooling to accelerate the speed and reach of analytics across the company. In this role, you'll partner with product and business leads to frame the most important questions, set the analytical bar, and ensure decisions across surfaces rest on a consistent, thorough foundation. You'll operate as a force multiplier - solving the hardest problems, building the frameworks others reuse, and levelling up data scientists across teams. WHAT YOU'LL DO: Be the DS tech lead across multiple product and business teams: setting methodological standards and unblocking the hardest analytical problems across areas including Treasury, Markets, Custody, and XRPL. Partner with product and business leads to define analytics strategy: shaping which initiatives to invest in, what success looks like, and how we'll know. Build the scientific frameworks Ripple reuses at scale: product and network health metrics, causal inference playbooks, liquidity and adoption models, and forecasting approaches that work across institutional and developer surfaces. Pioneer AI-accelerated analytics: applying LLMs and agentic workflows to scale insight generation, automate routine analysis, and enable self serve exploration for non-DS partners. Drive evidence based evaluation of growth across customers, corridors, and on chain activity, surfacing the causal drivers behind adoption and volume. Define and communicate the metrics leadership runs on: translating complex results into clear narratives for Ripple executives and external stakeholders. Raise the bar for the DS function through thought leadership and mentorship across embedded teams. WHAT YOU'LL BRING: 8+ years in data science or quantitative analysis, with a track record of senior level impact across multiple teams. Demonstrated technical leadership across cross functional teams, influencing roadmaps and strategy at both executive and execution levels. Proven experience designing reusable analytics and measurement frameworks that scale across products. Hands on experience applying AI to accelerate analytics workflows (agentic analysis, AI assisted insight generation, natural language data interfaces). Deep expertise in experimentation, causal inference, forecasting, and statistical modeling in a product environment. Expertise in Python or R, fluency in SQL, and experience with large scale data tech (Databricks, Airflow, dBT a plus). Experience with FinTech, payments, crypto, or blockchain data is a strong plus. Advanced degree (MS, PhD) in a quantitative field preferred. Exceptional communication skills - able to turn technical depth into executive ready narratives. WHO WE ARE: Do Your Best Work The opportunity to build in a fast paced start up environment with experienced industry leaders A learning environment where you can dive deep into the latest technologies and make an impact. A professional development budget to support other modes of learning. Thrive in an environment where no matter what race, ethnicity, gender, origin, or culture they identify with, every employee is a respected, valued, and empowered part of the team. In office collaboration for moments that matter is important to our culture, and we give managers and teams the flexibility to decide which 10+ days a month they come in. Bi weekly all company meeting - business updates and ask me any style discussion with our Leadership Team We come together for moments that matter which include team offsites, team bonding activities, happy hours and more! Take Control of Your Finances Competitive salary, bonuses, and equity Competitive benefits that cover physical and mental healthcare, retirement, family forming, and family support Employee giving match Mobile phone stipend Take Care of Yourself R&R days so you can rest and recharge Generous wellness reimbursement and weekly onsite & virtual programming Generous vacation policy - work with your manager to take time off when you need it Industry leading parental leave policies. Family planning benefits. Catered lunches, fully stocked kitchens with premium snacks/beverages, and plenty of fun events Benefits listed above are for full time employees. Ripple is an Equal Opportunity Employer. We're committed to building a diverse and inclusive team. We do not discriminate against qualified employees or applicants because of race, color, religion, gender identity, sex, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by local law or ordinance. Please find our UK/EU Applicant Privacy Notice and our California Applicant Privacy Notice for reference.

The Subscriptions mission helps people discover the right Spotify experience for them and supports the entire journey from free to paid. Our teams build products and services that make it easier for listeners around the world to understand the value of Spotify Premium while enabling sustainable growth for the business. The Markets & Subscriptions team oversees the entire user journey on Spotify and ensures we engage with people in innovative ways, every step of the way. Our team grows Spotify's audience by finding future listeners around the world and delivering the right value to them, at the right time. With research, product development, product design, engineering, and marketing all collaborating in one organization, we're able to quickly create meaningful features and services for millions of people around the world, resulting in joyful, long-lasting relationships with Spotify. We are looking for a Senior Backend Engineer to join our cross functional team of data scientists and mobile, web, and backend engineers to build the services that power Spotify's free-to-paid experiences. What You'll Do Collaborate with a cross-functional engineering team to build and evolve Spotify's subscription conversion experiences. Design and develop scalable backend services and APIs using Java, gRPC, and GCP. Partner with teams across the Subscriptions mission to support new products, plans, and global launches. Build resilient backend systems that support millions of users across web and mobile. Work closely with product managers and engineers to deliver technical solutions that solve meaningful customer and business problems. Lead technical initiatives while mentoring teammates and raising engineering quality across the team. Champion engineering best practices, operational excellence, and continuous improvement. Who You Are You thrive in collaborative environments and enjoy solving complex technical problems with others. You have 5+ years of experience building backend systems at scale. You have experience with Java, gRPC, and Google Cloud Platform (GCP). You know how to design APIs and backend services consumed by multiple client platforms. You care about writing maintainable, high-quality, production-ready software. You have experience working with internal stakeholders to build reusable platforms and services. Experience with subscription, conversion, commerce, or merchandising systems is a plus. Where You'll Be This role is based in London, England or Stockholm, Sweden. We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

JOB DESCRIPTION As a Lead Software Engineer for AI - Vice President at JPMorgan Chase in Risk Technology, you will lead a specialized technical area, driving impact across teams, technologies, and projects. You will leverage your expertise in software engineering, multi agent system design, data science, and NLQ to deliver complex, high impact initiatives. You will mentor and guide a team of engineers, foster best practices in AI engineering, and partner with data science, product, and business teams to deliver end to end solutions that drive value for the Risk business. Job Responsibilities Lead the deployment and scaling of advanced generative AI and agentic AI solutions for the Risk business, with a focus on natural language querying of structured and unstructured data sources. Design and execute enterprise wide, reusable AI frameworks and core infrastructure to accelerate AI solution development, including NLQ capabilities for diverse data types. Develop multi agent systems for orchestration, agent to agent communication, memory, telemetry, guardrails, and NLQ driven data retrieval and processing. Guide research on context and prompt engineering techniques to improve prompt based model performance and NLQ accuracy, utilizing libraries such as LangGraph. Develop and maintain tools and frameworks for prompt based agent evaluation, monitoring, and optimization at enterprise scale, with emphasis on NLQ workflows and orchestration. Build and maintain data pipelines and processing workflows for scalable, efficient consumption and querying of structured and unstructured data via natural language interfaces. Write secure, high quality production code and conduct code reviews. Partner with Data Science, Product, and Business teams to identify requirements and develop NLQ enabled solutions. Communicate technical concepts and results to both technical and non technical stakeholders, including senior leadership. Provide technical leadership, mentorship, and guidance to junior engineers, promoting a culture of excellence and continuous learning. Required Qualifications, Capabilities, And Skills Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. Experience in data science and natural language querying, including experience deploying end to end pipelines on AWS. Strong proficiency in Python. Hands on experience in system design, application development, testing, and operational stability. Experience using LangGraph for multi agent orchestration and NLQ integration. Experience with AWS and infrastructure as code tools such as Terraform. Preferred Qualifications, Capabilities, And Skills Strategic thinker with the ability to drive technical vision for business impact. Experience with agentic telemetry, evaluation services, and orchestration of NLQ workflows. Demonstrated leadership working with engineers, data scientists, and AI practitioners. Familiarity with MLOps practices and AI pipelines. Hands on experience building and maintaining user interfaces for NLQ and data exploration. Equal Employment Opportunity Statement We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Applied Engineer (Tribal Knowledge) Design and own the agent system that compiles an organization's tribal knowledge London / SF Full-time Engineering About Pavo Pavo is building Enterprise Superintelligence: compounding systems that take ownership of business outcomes and work with humans to deliver them. We believe that while foundation models are necessary, they are not sufficient. The hard problem is systems intelligence: end-to-end architectures that understand a company's code, data, and decisions, and improve themselves through experience. We are assembling a small, senior team of researchers and engineers obsessed with systems-first intelligence. Our current team consists of PhDs and ML engineers from top applied ML and coding agent companies, with a heritage of shipping systems at Spotify, ShareChat, and Sourcegraph scale. Our team has built impressive momentum with a small group of highly capable engineers and researchers. The Opportunity As an Applied Engineer at Pavo, you will design and own the agent system that compiles an organization's tribal knowledge - the body of knowledge that nobody has written down - from its own evidence: source code, structured data, internal documents, and conversations. You'll work hands-on at the level of agent architecture, pipeline design, and the production surface that turns a generative system into one customers can depend on. You'll partner closely with the Applied Scientist on instrumentation - but the system itself is yours. It is the most consequential thing we build, and idea to production is days. This is a senior, individual-contributor role. Everyone on the team joins as a Member of Technical Staff - with the scope, autonomy, and end-to-end ownership that title implies. What You'll Build Hierarchical Agent Architecture: Design how a main agent coordinates sub-agents, tools, and skills - deciding where deterministic scaffolding beats prompting and where prompting is the right tool. This decomposition is the single biggest determinant of whether a generative knowledge system is dependable. The Synthesis Pipeline: Own the multi-stage system that turns heterogeneous private evidence into a verifiable knowledge artifact - with the checkpoints, retries, fallbacks, and structured outputs that production reliability requires. Deployment & Rollout: Build scheduled regeneration, quality and reliability gates, blue/green rollout, and customer-facing version control of compiled knowledge artifacts. Treat each release with the seriousness it deserves. Observability & Debuggability: Structured traces of agent runs, replay/debug tooling, cost and latency budgets, and regression detection on releases. A multi-stage agent run must be debuggable by someone who didn't initiate it. Reliability as a First-Class Property: Treat run-to-run variance as a defect class equal to incorrectness, and build the engineering practice that reduces it. Eval & CI Infrastructure: Reproducible, automated evaluation that feeds signal back into the deploy loop - complementary to the experimental harness on the science side. What We Are Looking For We are looking for an engineer who has shipped dependable production systems and is hungry to do it at the edge of what current agentic frameworks can do. Core Qualifications Senior Track Record: 8+ years building and operating production systems, including a stretch where you owned a major system or platform area end-to-end and were the engineer others came to for the hard problems. Production Engineering Chops: You ship Python systems that other engineers want to extend; you write tests that catch real bugs; you have opinions about structure, dependency boundaries, and what belongs in a library versus an application. Hands On with an Agentic Framework: Depth with at least one - Anthropic tool use, OpenAI Agents SDK, Pydantic AI, LangGraph, AutoGen, or equivalent - including its sharp edges, not just its happy path. We have no preference for which; we strongly prefer that you've been bitten by one. Strong Opinions on Agent Architecture: When to use a single-context agent versus decompose into sub agents. Where deterministic code beats prompting, and how to tell which before the third refactor. What a tool is, what a skill is, and where the line is. Deployment Pipelines for ML/LLM Systems: Experience designing and operating rollout, gating, observability, on call posture, and regression detection. Comfort with Reliability Work: The unglamorous work that turns a flaky agent into a dependable one - async Python, structured outputs, retries with sensible idempotency, and the long tail of "why did this run produce a different answer." Pragmatism About Prompts: A hard won sense of what's prompt tunable and what isn't. You've earned this opinion at least once. Preferred Qualifications Built or maintained an LLM evaluation harness in production. Familiarity with retrieval / IR systems and the engineering of large-context pipelines. Distributed systems background - workflow engines (Temporal / Airflow / Prefect), queues, and observability stacks (OpenTelemetry, Datadog, Honeycomb). Open source contributions to agentic frameworks, eval tooling, or workflow orchestration. Why Join Us Architecture Defining Work: The system you design becomes the substrate for everything we ship downstream. Short Loop: Work directly with the Applied Scientist on instrumentation and with the founders on platform direction. Idea to production is days. Real Ownership: Genuine ownership in a small, technically deep team. Your name will be on the system. Foundational Space: The private knowledge layer will reshape how AI agents operate inside organizations; the engineering problems sit at the edge of what current agentic frameworks can do well. Pavo is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Job Title: Senior Director, Artificial Intelligence (AI) and Data Strategy, TOSI Reporting to: VP Technical Operations, Science & Innovation Location: Macclesfield, UK Hybrid working model - 3 days per week onsite At AstraZeneca, science compels us to push the boundaries of what is possible to turn science into life changing medicines for patients who need them most. We deliver breakthrough science by creating thriving, vibrant and open science centres where our scientists are free to pursue their ideas and collaborate both with colleagues and our academic and industry partners. Introduction to role: Are you ready to harness AI and data to reshape how life changing medicines are sustained at scale? In this role, you will set the vision and lead the execution of a bold AI and digital strategy that connects development to large scale technical operations, accelerating productivity, compliance, and problem solving across the commercial product lifecycle. You will lead a small, high performing team of AI and digital experts to deliver measurable impact-reducing cycle times, improving first time right outcomes, and embedding sophisticated analytics into daily decision making. If you can bring senior leaders together behind a clear and compelling roadmap, implement solutions that deliver lasting value, and build the capabilities that embed transformation for the long term, we would be delighted to hear from you. Accountabilities Vision and Strategy: Define and own the AI, data, and digital strategy for on market technical functions, aligned to business objectives and patient impact. Value Realisation: Drive measurable productivity gains and cost efficiencies; set benefit targets and ensure solutions translate to outcomes in the business. Portfolio Leadership: Build and manage a balanced portfolio of initiatives that redefine day to day operations, from pilot to scale. Indicators and Governance: Establish metrics, tracking mechanisms, and governance to ensure benefits are realised and sustained. Solution Delivery and Adoption: Lead the development, delivery, implementation, and adoption of digital and AI solutions that enhance efficiency and innovation across teams. Platform Integration: Partner with platform owners to integrate ERP, MES, QMS, and content/regulatory systems into end to end digital solutions. Data Architecture and Compliance: Shape robust data architectures and governance that enable AI at scale in regulated environments. Investment and Stakeholder Alignment: Create compelling business cases, align senior leaders, secure funding, and track the value delivered. Workforce Capability Uplift: Build a strategic capability programme that raises digital fluency and prepares the organisation for the future. Team Leadership: Lead and mentor a small team of AI/digital experts; foster a culture of innovation, delivery, and continuous improvement. Portfolio and Resource Management: Manage budgets, resources, and multi functional collaborations to meet commitments and influence outcomes. Safety, Quality and Standards: Champion SHE and cGMP principles while advancing digital transformation. Essential Skills/Experience Master's degree or equivalent experience or higher in a relevant science or engineering field. Technical expertise, including knowledge in the language of AI, data engineering, e.g., Python, R, cloud platforms (AWS/GCP). Solid understanding of data architecture, data governance, and AI deployment at scale in regulated environments. Experience working with enterprise platforms (e.g., ERP, MES, QMS, content/regulatory systems) and integrating them into digital solutions. Strong CMC knowledge with experience in Pharmaceutical Product Development and Manufacture, along with extensive knowledge of CMC processes across all product stages. Strategic leadership with a proven track record of developing, leading and delivering multi functional digital strategies and transformative programmes within a pharmaceutical CMC context. An innovative outlook that employs a digital first approach to streamline processes, enhance compliance, and foster efficiency. Outstanding business insight, proficiency in developing a strong argument for projects, organisational skills and lean tool deployment. Managing transitions and agility with ability to drive digital transformation and adapt strategy based on internal constraints or evolving tech/regulatory landscapes. Experienced in managing collaborators, good communication skills, capable of leading and collaborating effectively at senior levels. Ability to build consensus and navigate conflicts. A problem solving approach that delivers critical thinking and substantial business value. Thorough understanding of principles, applications and management of SHE and cGMP. Desirable Skills/Experience PhD or equivalent experience in a relevant scientific, engineering, or data field. Demonstrated experience operationalising MLOps, model lifecycle management, and validation in GxP contexts. Familiarity with generative AI, knowledge graphs, semantic layers, and digital twins for manufacturing and CMC. Experience leading global, multi functional teams and vendor ecosystems across multiple time zones. Knowledge of ICH guidelines (e.g., Q8-Q12) and regulatory interactions related to digital/AI enabled submissions. Track record of thought leadership (e.g., publications, conference talks, patents) on AI and data in CMC. Certification in Lean Six Sigma or portfolio/program management. Experience spanning both small molecule and biologics would be advantageous. Date Posted 25-Jun-2026 Closing Date 24-Jul-2026 Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.

Graduate Data Scientist Location: UK (London-based) Hybrid working: 3 days in the office Are you passionate about using data science, AI and analytics to solve real-world business challenges? At Branding Science Group, we're looking for a motivated Graduate Data Scientist to join our growing global Data Science team. Working at the intersection of data science, healthcare insights, technology and innovation, you'll help drive meaningful business change through automation, analytics and AI-powered solutions, while developing your technical expertise in a supportive and collaborative environment. What You'll Do Support data science initiatives that drive key business outcomes Assist in delivering our data strategy and improving access to internal data assets Build, maintain and enhance internal data science tools, pipelines and AI-powered applications Perform quantitative data analysis for client projects Identify and implement automation opportunities to improve business efficiency Support the rollout and adoption of new data and AI tools across teams Contribute to thought leadership activities, including LinkedIn content and conference presentations Help improve AI literacy and data science capabilities across the organisation Provide regular updates and reporting to senior team members What You'll Bring A Bachelor's, Master's or PhD in Mathematics, Statistics, Data Science or another numerate discipline A strong interest in applying data science to solve business problems Experience contributing to analytical, technical or machine learning projects through academic, internship or personal projects Understanding of statistical concepts including hypothesis testing, regression and p-values Experience coding in Python or R for data analysis, modelling or visualisation Strong analytical thinking and problem-solving skills Excellent communication skills with the ability to explain technical concepts to non-technical audiences Strong organisational and time-management skills A proactive mindset, curiosity to learn and high personal integrity Desirable Experience Experience building code-based technical solutions Exposure to AI or LLM applications (e.g. OpenAI or Anthropic APIs) Experience using Git or other version control systems Exposure to data pipelines, APIs and SQL databases Experience deploying internal or web-based data tools Why Branding Science Group? Join a collaborative, forward-thinking team that combines data science, AI, healthcare expertise and strategic insight to help clients and colleagues make better decisions. You'll have the opportunity to work on meaningful projects, develop in-demand technical skills, collaborate with global colleagues, and play a role in shaping the future of data science and AI at Branding Science Group. If you're ready to launch your career in data science and make a real impact

Job Title: Senior Python Developer Contract type: Contractor Contract hours: Full-time Location: Remote (within 2 hours of London timezone) Salary: €60k - €70k About Adzuna Adzuna is a job search engine that lists every job, everywhere. From our launch in the UK in 2011, we now have tens of millions of visitors a month and are busy conquering the world from our HQ in West London alongside our remote teams - helping millions of people find better, more fulfilling jobs. We already have a suite of AI-powered tools (such as ValueMyCV, Prepper and ApplyIQ) built by our talented team and their passion for building new AI-powered tech for job seekers. We're a commercially minded team that moves fast, takes ownership and loves what we do. About the Role This is a fantastic opportunity for a high-impact Senior Python Developer and Tech Lead to join our fast-moving team. In this pivotal leadership role, you will work closely with our Head of Tech/AI coding to migrate this team and the technology they own to a single, high-performing team working on our new Python-based platform using Agentic AI coding techniques. You will provide technical stewardship across our full stack, architecting robust backend services and guiding the development of cutting-edge AI products. Working alongside Product Managers and Data Scientists, you will lead the transition of machine learning prototypes into production-ready applications for millions of users, while mentoring engineers and driving the long-term technical strategy for our AI-powered tools. What You'll Do Technical Leadership & Mentorship: Act as a tech lead in one of our tech teams, unifying disparate development silos and fostering a culture of excellence through code reviews, architectural guidance, and mentorship of a small team of engineers. Architectural Stewardship: Lead the design and implementation of scalable backend API endpoints and LLM pipelines, ensuring the seamless integration of agentic frameworks into our production stack. Data Strategy: Architect high-throughput data pipelines to move clean, processed data between databases and user interfaces, maintaining system integrity and performance. Infrastructure & Security: Engineer secure infrastructure for user authentication, session persistence, and memory caching while optimizing AWS environments for high availability. Strategic Execution: Drive the migration from legacy systems to our new Python stack, making critical decisions on maintenance mode vs. new development to maximize business value. Tech Stack Includes: Languages & Frameworks: Python, Spark, LLMs & LLM coding tools Frontend: React, HTML, CSS (Tailwind) AWS Ecosystem: EC2, S3, Lambda, Step Functions, RDS, Athena, Kinesis Databases & Search: PostgreSQL, MySQL, SOLR While we look out for all of these skills, we do not expect experience in all of them. We value a strong foundation in core programming principles and a genuine eagerness to learn. Experience: Extensive commercial software development experience with a focus on Python, including a proven track record in technical leadership or lead developer roles. Location: Fully remote (must be located within a 2-hour timezone of London and able to work standard UK business hours). Right to Work: This is a permanent, long-term role structured via a contractor agreement for international remote compliance. Candidates must have the legal right to work remotely as an independent contractor in their country of residence. We are unable to provide visa sponsorship for this position now or in the future. Communication: Professional proficiency in English (both written and verbal) to collaborate effectively with a global team. Education: A technical degree (2:1 or equivalent) in Computer Science, Software Engineering, or a highly relevant field. Core Coding Skills: Strong understanding of Python fundamentals and object-oriented programming. Execution: Record of writing clean, maintainable Python code into live, user-facing environments. Databases: Strong expertise in MySQL and/or PostgreSQL and relational databases. Cloud & Tools: Familiarity with AWS services and Git version control. Strategic Mindset: A results-driven thinker who focuses on commercial outcomes and can serve as a subject matter expert for senior leadership regarding the Python ecosystem and AI/ML frameworks. AI Applications: Experience with coding LLMs into production applications, and effectively utilising agentic AI coding in your daily workflow. Nice to have: Frontend Coding Skills: Familiarity with HTML, CSS (Tailwind) and React to assist in building fullstack user interfaces. Browser Automation: Understanding of web scraping techniques, DOM parsing, and bypassing common bot-detection. Experience with browser automation and testing tools (e.g. Playwright, Selenium). Portfolio: An active GitHub profile showcasing examples of your work, or personal projects. Reward: Our package which includes a competitive salary and stock options (we are all owners!). Wellbeing: Amongst other things, enhanced maternity and paternity leave; 25 days paid holiday per year plus 8 bank holidays; 3 paid volunteer days/year; Summer hours through July and August (we finish at 4pm on a Friday); and a full programme of wellbeing activities and events. Hybrid working: We are a fully hybrid company - half our workforce is remote. With employees located in different time zones, we embrace asynchronous work and ensure that everything we do reflects the hybrid nature of our workforce so that everyone feels included. In addition, we have a travel programme, to help facilitate effective hybrid working. Diversity & inclusion: We are committed to hiring a diverse workforce and creating an environment where everyone feels included and welcome. Our D&I committee helps deliver a programme of activities and actions to support this important area. Training: Learning and development is an important pillar of our culture and there are plenty of opportunities to learn, develop and grow whether through our Adzuna Academy training programme, attending conferences, team training budgets, individual development plans and coaching from experienced and supportive peers and managers. Fun stuff: We have a packed social calendar, twice yearly global team get-togethers and an enviable culture thanks to the amazing and smart people who make Adzuna a great place to work. Lots of this is done virtually to ensure that everyone is included. A bit more about Adzuna Adzuna is an established and profitable job search engine that lists every job, everywhere. Launched in 2011, we help over 10 million visitors a month in 19 markets find better, more fulfilling jobs. Governments and the world's largest companies trust us for our unique global audience and jobs market intelligence, and we walk the walk on things like salary transparency and gender pay. Adzuna's success to date has been down to the skills and determination of our brilliant staff and their passion for job seekers. If you like the sound of applying your skills in a pivotal role in a leading global technology business, apply to join us today. We treat jobseekers as people, not as products. We do the same for our team, seeing the diverse range of strengths they bring to our business. Regardless of background, race, gender, sexuality or ability, we welcome everyone to our team. Our people are the most important asset we have. Please let us know if we need to accommodate a disability during the hiring process, so that we can give you the support you need. Proud member of the Disability Confident employer scheme.

Funding End Date 31 Aug 2028 Hours per week 37 Project Title Senior Project Software Developer (COPO) Months Duration 24 Flexible Options Although full-time hours are available, applications from those interested in working part-time hours are also welcomed. Job Description Main Purpose of the Job The Earlham Institute is seeking a versatile full-stack Research Software Engineer (RSE) to join the team behind COPO (Collaborative OPen Omics). COPO is a production-deployed metadata and data-brokering platform that has been developed and operated at the Institute since 2015. COPO underpins some of the largest biodiversity genomics programmes attempted to date, having brokered more than 80,000 samples from over 4,800 species to public repositories such as the European Nucleotide Archive, with automated validation, expert curation and full audit trails. The successful candidate will join the small engineering team that builds and operates COPO, contributing across the full stack -frontend interfaces, APIs, and the services that connect them to the platform's validation, curation and submission pipelines. Data visualisation, dashboards and API design will be at the centre of the role, but the post is deliberately broad: COPO supports a range of research communities and projects, and the work varies with the needs of those the platform serves. This is a broadly scoped full-stack role with metadata validation, translation, visualisation and API design as its primary focus. It suits an engineer who enjoys turning complex scientific data into clear, reliable, well-documented interfaces that researchers and the wider community can depend on. Being a senior, hands-on role, you will own significant components of the project end to end, make day-to-day architectural decisions, and drive delivery to time. Key Relationships Internal: COPO Team Lead / Group Leader (direction, prioritisation, line management); the COPO development team of fellow engineers and frontend developers (collaboration, code review, and mentoring); EI bioinformaticians and research scientists (scientific and metadata requirements); Scientific Computing / IT infrastructure teams (compute, storage and platform services); and project managers / programme coordinators (planning, reporting and effort estimates). External: genomics and biodiversity programmes and projects that COPO supports; EMBL-EBI / ELIXIR services such as ENA and BioSamples; other public repositories and registries such as Zenodo and DataCite; metadata-standards communities including RO-Crate, ISA, MIxS, Darwin Core and Bioschemas; and the wider open-source community and downstream COPO users. Main Activities & Responsibilities Dashboards, data visualisation and data portals Design, build and maintain interactive dashboards and public data portals, from data model through to production deployment. Translate complex, multi-source scientific metadata into clear, accurate and accessible visualisations. Build reporting and summary views that are reproducible and auditable, including snapshots for governance and reporting. Apply good practice in accessibility, responsive design and information design so that outputs are usable by researchers and the public alike. APIs and backend services Develop, document and maintain RESTful APIs that expose metadata in multiple formats for internal tools and external consumers. Integrate frontend and portal services with COPO's validation, curation and submission pipelines. Ensure APIs are performant, versioned, secure and well documented so third parties can build against them with minimal support. Full-stack engineering and platform contribution Contribute across the COPO codebase: frontend, backend and supporting services as a flexible member of a small engineering team. Write clean, tested, maintainable code with appropriate use of version control, code review, CI/CD and containerisation (Git, Docker). Help deploy and operate COPO instances, working with colleagues on deployment, monitoring, backup and reliability. Collaboration, standards and support Work closely with the technical lead and engineering colleagues to extend the platform and its metadata standards. Help add support for new data types and metadata schemas, and reflect these in the interfaces and APIs you build. Support research users onboarding onto the platform, including documentation, tutorials and responsive help. Produce clear technical documentation and contribute to open-source releases under permissive licences. As agreed with line manager, any other duties commensurate with the nature of the role. Person Profile Education & Qualifications Requirement Importance Degree (or equivalent professional/practical experience) in computer science, software engineering, bioinformatics or a related discipline Essential Specialist Knowledge & Skills Requirement Importance Proficiency with version control (Git) and collaborative development workflows, including code review Essential Understanding of FAIR data principles, ontologies or controlled vocabularies Essential An understanding of, and willingness to apply, good engineering practice: automated testing, clear documentation and basic security awareness Essential Able to translate complex requirements into clear, usable interfaces, with strong attention to accuracy and detail Essential Familiarity with cloud or research-computing infrastructure Desirable Exposure to genomics, biodiversity, ecology or a related life-science domain Desirable Requirement Importance Demonstrable experience building and maintaining full-stack web applications in JavaScript and a backend language (Python preferred) Essential Experience designing, building and documenting RESTful APIs Essential Experience with containerisation and deployment (Docker; CI/CD pipelines) Essential Experience designing and building data visualisations or dashboards, using libraries such as Plotly, D3, or equivalent Desirable Experience working with structured or scientific data, metadata standards, or data-intensive systems Desirable Management and Leadership Requirement Importance Experience mentoring, coaching or line-managing other developers Essential Interpersonal & Communication Skills Requirement Importance Committed to open, reproducible and well-tested software Essential Able to work both independently and as a flexible, collaborative member of a small team Essential Good written and verbal communication skills, including the ability to produce clear technical documentation and explain technical matters to non-specialists Essential Comfortable working with, and responsive to, a distributed community of research users Essential Able to work independently, use initiative and apply problem solving skills Essential Additional Requirements Requirement Importance Promotes equality and values diversity Essential Attention to detail Essential Willingness to embrace the expected values and behaviours of all staff at the Institute, ensuring it is a great place to work Essential Able to present a positive image of self and the Institute, promoting both the international reputation and public engagement aims of the Institute Essential Willingness to work outside standard working hours when required Essential Ability to maintain confidentiality and security of information where appropriate Essential Who We Are About the Earlham Institute The Earlham Institute harnesses the power of data-driven biology to accelerate solutions for health, biodiversity, and food security. Based at Norwich Research Park, the Earlham Institute is one of eight institutes strategically funded by BBSRC. Our science combines world-class technology, interdisciplinary expertise, and training and development across genomics, engineering biology and data science, to decode the scale and complexity of living systems. We believe we can achieve more if we work together. That's why we collaborate with the global science community and industry partners, while also inspiring the next generation of scientists and technical specialists. Our Science Earlham Institute scientists specialise in developing and testing the latest tools and approaches needed to decode living systems and make biological predictions. We are home to state-of-the-art facilities and technology, creating a unique combination of expertise and infrastructure. We have dedicated laboratories for genome sequencing, single-cell analysis, engineering biology, and large-scale automation; as well as one of the largest supercomputing facilities for life science research in Europe. Our Advanced Training team also provides access to specialised scientific training to upskill the next generation of research and technical staff. Our Culture Our collegiate and innovative research environment comes with significant support, including a commitment to your professional development, research and administrative assistance, and opportunities to build collaborations with scientists and industry on the Norwich Research Park, across the UK, and internationally. The Institute is also home to talented technical and operational staff, whose invaluable contributions enable our science to have the maximum impact. We aim to recognise, reward, and develop all staff and students so that every individual feels able to achieve their best with us. We work hard to nurture an engaged and positive workplace, centred on core values that include openness, technical excellence, and collaboration . click apply for full job details

The Earlham Institute in Norwich, UK invites applications for a (Senior) Research Software Engineer - AI Co Scientist Systems. The role spans SC5/SC6 levels, focusing on designing and building an AI agent platform connecting models, datasets, and lab automation. The post is based in Norwich with access to substantial GPU compute and collaborative research across EI groups. You will contribute to publishable AI systems, open source software, and demonstrators, shaping human AI interaction for

(Senior) Research Software Engineer - AI Co-Scientist Systems Job Title (Senior) Research Software Engineer - AI Co-Scientist Systems Post Number Closing Date 20 Aug 2026 Grade SC6/SC5 Starting Salary Salary: £38,000-£52,560 Hours per week 37 Project Title Generative Digital Biology: AI Co-Scientist Systems and Lab Automation Expected/Ideal Start Date 07 Sep 2026 Months Duration 36 Job Description Main Purpose of the Job The post holder will take a research-active software engineering and AI systems role in the AI for Biology Group, building the AI-agent-driven platform required for Generative Digital Biology. The role will connect foundation models, scientific tools, biological datasets, experimental design algorithms, lab automation workflows, robotics interfaces and human in the loop scientific decision making. This is a platform building research role, not a conventional bioinformatics software support post. The successful candidate will contribute intellectually to research, develop publishable AI systems, build open source software and demonstrators, co author research outputs and support competitive grant applications. The role would suit a highly capable computer scientist, AI systems researcher, robotics engineer or research active software engineer who wants to build the technical backbone for AI driven biological discovery. A key objective will be to develop an AI co scientist demonstrator for the group and the Institute: a platform that can show how AI agents can interact with human scientists via virtual/augmented reality, reason over biological questions, call scientific tools and APIs, use foundation models, design experiments, interface with computational and physical workflows, and support rigorous, auditable and reproducible scientific discovery. The post holder will work closely with the other AI for Biology appointments. Foundation model research in the group will provide biological representations and predictive models; generative and causal AI research will provide design and experimental decision algorithms; this RSE role will build the software, agentic workflows, tool registries, automation interfaces, provenance mechanisms and demonstrator environment that connect these components into a usable scientific discovery system. This will be a highly collaborative role embedded across EI. The post holder will work with EI colleagues and platforms to connect AI designed hypotheses and candidates with biological data, experimental design and validation routes, including potential collaborations with Earlham Biofoundry and engineering biology colleagues on AI-guided design build test learn cycles; with Cellular Genomics and Single cell and Spatial Analysis on perturbation, cell state and single cell/spatial omics use cases; and with BioFAIR, ELIXIR UK, Open and FAIR Data and Research e Infrastructure colleagues on AI ready design datasets, benchmarks, provenance and reproducible workflows. Prior experience in lab automation is desirable but not essential. We particularly welcome candidates with exceptional computer science, large scale machine learning systems, robotics or software engineering backgrounds who are motivated to apply their skills to biological discovery and to learn the relevant biological and automation context. Key Relationships INTERNAL: Reporting to Professor Ke Li, the post holder will work closely with the AI for Biology Group and collaborate across EI's research programmes, National Bioscience Research Infrastructures, Research e Infrastructure and technology platforms. Key internal relationships are expected to include Earlham Biofoundry and engineering biology colleagues for lab automation, robotics interfaces and design build test learn workflows; Research e Infrastructure for HPC/GPU/cloud, reproducible software and scalable model deployment; BioFAIR, ELIXIR UK and Open and FAIR Data colleagues for AI ready resources, provenance, data/model documentation and interoperable workflows; Cellular Genomics and Single cell and Spatial Analysis for biological use cases; and relevant EI groups working on plants, microbes, biodiversity, health, genomics and data intensive bioscience. EXTERNAL: The post holder will interact with UK and international collaborators in AI, AI agents, machine learning systems, research software engineering, robotics, laboratory automation, autonomous experimentation, computational biology, engineering biology, genomics, plant science, human health and therapeutic discovery. External collaborations may include academic, public sector, infrastructure, clinical and industry partners where appropriate. Main Activities & Responsibilities Design and build the AI Co Scientist system/software architecture for the GDB programme, including agent orchestration, tool registries, model interfaces, workflow execution, data/model versioning and provenance tracking. For appointment at SC5, take technical and operational leadership of a defined AI Co Scientist platform or workstream; own the architecture, roadmap, milestones and technical risk decisions; and deliver the work with limited supervision (essential for SC5). 20 Develop AI agent workflows for scientific reasoning, literature/data retrieval, tool use, planning, hypothesis generation, experimental design, result interpretation, iterative refinement and human in the loop decision making. 15 Build software interfaces connecting AI agents with biological datasets, foundation models, generative models, Bayesian experimental design, optimisation algorithms, benchmarking tools and HPC/GPU/cloud resources. For appointment at SC5, coordinate cross platform integration, define interface contracts and engineering standards, resolve technical dependencies, and ensure coherent delivery across AI, data, infrastructure and automation partners (essential for SC5). 15 Develop interfaces to lab automation, robotics, biofoundry workflows, instrument control APIs, LIMS/ELN systems, digital twin/simulation environments or related physical AI workflows where appropriate. 15 Build an interactive AI Co Scientist demonstrator environment for research, collaboration, grant development and institutional showcase purposes. 10 Implement robustness, safety, permissioning, sandboxing, audit trails, provenance, reproducibility, monitoring and responsible use/dual use aware controls for AI systems operating in biological contexts. For appointment at SC5, define and lead implementation of software quality, testing, security, provenance, auditability and safe tool execution standards, including design/code review and release readiness decisions (essential for SC5). 10 Contribute intellectually to research papers, conference submissions, technical reports, open source software releases, demonstrations, presentations and community resources. For appointment at SC5, lead major software releases, demonstrators and technical/research outputs, and represent the work in relevant internal and external forums (essential for SC5). 10 Contribute to collaborative projects, competitive grant applications, documentation, testing, responsible data handling and long term platform strategy for the AI for Biology Group. For appointment at SC5, make substantive contributions to grant development and long term platform strategy, and provide technical guidance or mentoring to junior researchers or engineers (essential for SC5). 5 As agreed with line manager, any other duties commensurate with the nature of the role. Person Profile Education & Qualifications Requirement Importance PhD, or equivalent research or industrial experience at a comparable level, in Computer Science, AI, Robotics, Machine Learning, Software Engineering, Scientific Computing, Data Science, Computational Biology or a closely related quantitative discipline Essential Specialist Knowledge & Skills Requirement Importance Strong hands on software engineering ability, evidenced through substantial implemented systems, research software, open source code, AI/ML platforms, robotics/automation software or scientific computing projects Essential Experience designing, implementing and maintaining complex research software systems, AI systems, agentic workflows, robotics/automation software, scientific platforms or data intensive computational infrastructure Essential Experience with modern AI systems or scientific computing systems, such as large language models, tool-using agents, retrieval augmented generation, workflow orchestration, model APIs, machine learning frameworks, and the ability to develop agentic workflows for scientific applications Essential Understanding of, and commitment to, trustworthy AI, robustness, safety, provenance, auditability, sandboxing, permissioning, monitoring or dual use aware AI workflows for biological applications Essential Ability to build robust, maintainable and reproducible software using version control, testing, documentation, containers, APIs, databases, workflow tools, CI/CD and deployment on HPC, GPU, cloud or distributed computing environments Essential Demonstrable practical experience designing and building AI-agent, multi agent or scientific agent systems, including relevant experience in orchestration, tool use and evaluation (essential for SC5) Desirable Experience with robotics, lab automation, self driving laboratories, autonomous experimentation, instrument control, liquid handling platforms, automated microscopy, microfluidics, sequencing workflows, biofoundry platforms, ROS/ROS2 or related hardware/software integration Desirable Experience with biological data, genomics, single cell data, imaging . click apply for full job details

The Earlham Institute in Norwich seeks a versatile Senior Developer to join COPO. You will work across the full stack-from dashboards to APIs and data pipelines-transforming complex biodiversity data into reliable, well-documented interfaces used by researchers and the wider community. You will own significant components end-to-end, influence architectural decisions and collaborate with scientists and engineers to deliver robust, scalable solutions within a busy genomics research setting.

Closing Date 2026-07-31 Job Title: Data Engineer Location: Durrington, Worthing (Hybrid/Flexible) Contract Type: Permanent Hours: 37 Salary: Up to £47k depending on skills and experience About the role: We're looking for a Data Engineer to join our Data & Analytics team as we embark on an exciting transformation in how we manage and use data across Southern Water. This role sits at the heart of our data strategy, helping to improve how we manage, govern and utilise data to drive better outcomes for our customers and the business. Working within a collaborative, forward-thinking team, you'll play a key role in building and scaling our modern data platform on Microsoft Azure. What you will be responsible for: As a Data Engineer, you'll design, build and optimise data solutions that enable secure, scalable and high-quality data across the organisation. Build and maintain ELT pipelines to ingest, transform and load data into the Southern Water Delta Lake Automate and manage data pipelines using Azure Data Factory and Databricks, ensuring reliability and performance Design and implement scalable data models to support analytics, reporting and machine learning use cases Apply data governance, quality and security best practices using tools such as Unity Catalog, Purview and Key Vault Collaborate with data scientists, analysts, DevOps and business stakeholders to deliver aligned data solutions Monitor, troubleshoot and optimise data pipelines to improve performance, scalability and cost-efficiency Additional Requirements specific to the role Hybrid working with occasional travel to Durrington office Participation in team collaboration and delivery sessions as required No regular standby or rota requirements What you'll bring to the role: Essential Experience working with Azure data services including Databricks and Azure Data Factory Strong programming skills in SQL and at least one of Python, Scala, Bash or PowerShell Proven experience in data engineering, including building pipelines, data modelling and working with large datasets Understanding of data warehousing principles, big data architectures and performance optimisation Strong analytical and problem-solving skills with the ability to deliver complex solutions Desirable Microsoft Certified: Azure Data Engineer Associate or Azure Fundamentals Databricks Data Engineer certification or experience working in a similar environment Southern Water is at the forefront of transforming Britain's water industry, investing significantly to enhance resilience, sustainability, and service excellence. With £7.8bn planned investment for 2025-30, this is an unparalleled opportunity to join a business committed to delivering a generational shift in the way water services are managed. You will be joining at a timesignificant change, working alongside a highly skilled leadership team with a clear vision for the future. We offer an environment where senior professionals can make a meaningful impact, influence major strategic decisions, and drive long-term value creation At Southern Water, we believe diverse perspectives drive innovation. If you're passionate about making a positive impact and think you can bring value to our team, we'd love to hear from you-even if you don't tick every box. Your unique skills and experiences could be exactly what we need. Additional information: In line with Southern Water's security requirements, successful candidates will be required to provide evidence of their identity, eligibility to work in the UK, criminal record check (DBS) and verification of their employment and/or education history for the past three years. Appointment to this role is subject to the successful completion of all pre-employment checks, including security vetting. Please note that if a candidate does not meet the required security standards or fails to pass the vetting process, Southern Water reserves the right to withdraw the offer of employment. Some positions may also require higher levels of security vetting, which may involve providing additional documentation.

Senior/Lead Data Scientist -Credit Risk ModelingJob detailsData ScienceLondonFull-time£81,425 GBP - £116,438 GBPAt Klarna, our credit risk models sit at the heart of how we underwrite and price risk for millions of consumers globally. We're looking for a Lead Data Scientist to help shape the next generation of consumer-level credit scoring and portfolio valuation models. What you'll do As a Lead Data Scientist within credit risk modeling, you will shape Klarna's next-generation consumer-level credit scoring and portfolio valuation models. You'll design and maintain real-time PD (Probability of Default) models using statistical and ML approaches, integrating them into frameworks for underwriting and economic return optimization. You'll develop calibration frameworks, ensure compliance with regulatory and fairness standards, and explore novel methodologies - including LLMs for explainability and feature engineering. Collaborating with cross-functional teams, you'll translate modeling insights into strategic credit policies and business value, while mentoring junior team members and contributing to Klarna's long-term modeling vision. Who you are 5+ years' experience in credit risk modeling for consumer lending, credit cards, or BNPL. Deep proficiency in PD model development and validation, with strong knowledge of calibration techniques. Advanced Python and SQL skills; familiar with XGBoost, scikit-learn, pandas, MLFlow. Experience with explainability frameworks such as SHAP, LIME, PDP. Ability to communicate technical concepts clearly and influence cross-functional decisions. Familiarity with real-time modeling and current trends in ML and credit analytics. Awesome to have Hands-on experience using LLMs to extract features from unstructured data (e.g., customer communications, credit applications). Knowledge of integrating third-party credit bureau data into production models. Understanding of champion/challenger model frameworks and A/B testing infrastructure. Exposure to loan-level economic modeling, including cost-of-capital and loss metrics.Please include a CV in English

Are you a Data Scientist who's worked within a credit risk, lending, banking, fintech or consumer finance environment previously? Can you create compelling reports that tell a story and explain complex data sets to all audiences? Do you have the experience and drive to help establish and develop our data science and credit risk modelling capability from the ground up? About the Role. We're looking for a highly skilled and motivated Data Scientist to join us during an exciting time of Change and Transformation. Reporting to the Credit Risk Manager and working closely with the Director of Credit Risk and Data Analytics, this is a unique opportunity to become one of the key architects of our future decisioning and risk management framework. What You'll Do. You'll be responsible for developing our first generation of predictive credit risk models, including Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), application scorecards, affordability models and collections strategies. You will work with large and complex datasets to identify opportunities that improve lending decisions, enhance customer outcomes and support sustainable portfolio growth. Combining traditional data science techniques with practical commercial application, you'll leverage modern analytics, machine learning and AI-assisted development tools to accelerate model development, improve decision making and deliver tangible business value. You'll collaborate with stakeholders across Credit Risk, Operations, Finance, Collections and Technology to deliver innovative, data-driven solutions that support the company's strategic objectives and will use your quantitative skills to deliver actionable insights to a variety of senior external and internal stakeholders. Responsibilities Design, develop, validate and monitor predictive credit risk models including but limited to ECL, pricing, forecasting and provisioning models. Maintain application scorecards, affordability models and decisioning strategies that support responsible lending and portfolio growth. Support the development of provisioning, forecasting and portfolio monitoring methodologies. Analyse customer, bureau, affordability and behavioural data to identify trends, risks and opportunities. Utilise machine learning and AI-assisted development techniques to accelerate model development and improve analytical efficiency. Produce robust model documentation, validation reports and governance materials. Work closely with Credit Risk, Operations, Transformation and Finance teams to translate business problems into analytical solutions. Build scalable analytical processes using BigQuery, Python and Google Cloud technologies. Develop clear and insightful visualisations and presentations for both technical and non-technical audiences. Stay informed of industry best practice, emerging technologies and regulatory developments relevant to consumer credit risk modelling. Collaborate with stakeholders across departments to understand their data needs and deliver tailored solutions. Ensure data integrity and compliance with relevant regulations (e.g., GDPR). Identifying and analysing causes of urgent defects and making predictions on likelihood of recurrence Acting as an internal consultant to the business on data driven decision making and insights Developing differentiated pricing models and educating stakeholders on findings Discovering trends and patterns within complex data and present findings to stakeholders Leveraging state-of-the-art data mining and machine learning tools and methodologies to drive improved business decisions Documenting and articulate key learnings from the data mining exercises Your Working Style and Experience. You're proactive with excellent stakeholder managements skills, a confident presenter and someone who stays informed about emerging technologies and methodologies. You've experience of using Python, a strong knowledge of SQL, a solid understanding of statistical modelling techniques and predictive analytics, and experience developing, validating or monitoring predictive models and scorecards. About Billing Finance We are a privately-run family owned vehicle financing Company based on the outskirts of Northampton. We focus on customers with non-standard credit profiles that may not fit the automated underwriting processes of other lenders. Our mission is to help get all our people, including customers and staff " where they need to be " by " putting them at the heart of everything we do " . We are entering an exciting phase of transformation and as a small company, this role will offer the successful candidate the opportunity to work across the whole customer journey cycle, and to directly see the impacts that they made. Our values are: We are responsible - We are conscious of our impact on people and planet We care about you - We are kind and compassionate with our customers and with each other We work with you - We support financial wellbeing for our customers and the wider community The successful candidate will not only have a successful and fulfilling career with us but will also receive a fantastic range of benefits: Discretionary bonus scheme Electric Vehicle salary sacrifice scheme Pension salary sacrifice scheme Private Medical Income Protection Employee Assistance Programme The Recruitment Process and How We Will Use Your Data The recruitment process will involve obtaining information and/or exchanging it with the following organisations to assist with our pre-employment checks prior to interview. Credit Reference Agencies - to complete a soft credit check to understand your financial history CIFAS - to check both National and Internal databases for fraudulent activity. The personal information we have collected from you will be shared with Cifas who will use it to prevent fraud, other unlawful or dishonest conduct, malpractice, and other seriously improper conduct. If any of these are detected, you could be refused certain services or employment. Your personal information will also be used to verify your identity. Further details of how your information will be used by us and Cifas, and your data protection rights, can be found here . To complete these checks, you will be asked to provide your address history for the past six years, along with your full name and date of birth. The successful candidate will be required to undergo a Basic DBS check to comply with our FCA compliance framework. A satisfactory Basic Disclosure showing no unspent convictions is a prerequisite for this position. We may also ask for proof of your right to work status or evidence of any qualification or experience prior to being offered employment. Further information on how we collect and use your data during the recruitment process can be found in our Privacy Policy here Billing Finance is an equal opportunities employer, and we understand that for some candidates to perform their best they may need some reasonable adjustments. If we can make your application journey with us more suitable for you, please do let us know and we will endeavour to help.

A warehouse is an optimisation problem in a trench coat. Layouts, slotting, labour shifts, pick paths, replenishment - the difference between a good answer and a great one moves real money for every operator WareBee serves. As Data Scientist (Optimization Science) you will reach for linear programming, mixed-integer programming, constraint satisfaction, heuristic search, and simulation, and pick the right one for the problem in front of you. WareBee runs on two engines: Physical AI - a living, spatial model of the warehouse floor, its racks, aisles, and movement - and Process AI, which learns how work actually flows through it. Your optimisation work sits on top of both. What you will do Sit with operators and the product team, understand the real constraints, and turn fuzzy operational pain into formal models Solve real instances - at production scale, with messy warehouse data, against deadlines that matter Build solvers and heuristics that ship, not papers that don't Pair with engineers to embed solvers behind clean APIs and feedback loops Validate against the truth (operations on the ground), not just against the model What we are looking for Strong foundations in operations research, mathematical optimisation, or applied mathematics Production experience with at least one solver ecosystem and one general-purpose programming language Comfort with messy real data, partial information, and changing constraints Pragmatism about when an optimal solution is overkill and a heuristic ships Curiosity about the operational domain - logistics, supply chain, warehousing Hands-on warehouse, logistics, or supply-chain experience - you've seen how a real floor runs (a strong plus) What we offer Real operational problems with real money on the table A small senior team that respects the craft Hybrid in Cambridge, UK or Tel Aviv, Israel - or fully remote