Full job description

Are you a Senior Data Scientist who’s moved beyond traditional modelling into LLMs, GenAI, and production AI systems?
I’m hiring for a Senior Data Scientist to join a high-impact AI team within a leading consumer-focused organisation. This is a hands-on, end-to-end AI role working on large, complex, unstructured problems - building real products, not proof-of-concepts.
The companyA well-established organisation in the consumer health / insurance space, offering products that combine financial services with incentives for healthier living (including subscription-led rewards models).
Data and AI are central to how the business operates, with strong investment and leadership visibility - giving this team real ownership over innovative, business-critical solutions.
Where you fitYou’ll sit within a specialist AI team, working alongside both classical data scientists and AI engineers.
This team focuses on:
*LLMs, GenAI, and agentic workflows
*Solving unstructured, complex problems
*Building AI products used across underwriting, claims, customer experience, and more
Expect to work on 1-2 major projects, with high-impact, end-to-end ownership.
What you’ll be doing*Build and deploy LLM-based applications, including RAG systems, chatbots, and agentic workflows
*Apply traditional ML techniques (e.g. regression, classification, gradient boosting) where appropriate
*Design and deliver end-to-end AI systems from discovery to production
*Develop agentic workflows across areas like underwriting and claims
*Work closely with business stakeholders to define requirements and shape solutions
*Deploy models using modern MLOps practices (APIs, microservices, CI/CD, containers)
*Collaborate with engineers, product teams, and senior stakeholders across the business
Tech stack*Python & SQL (essential)
*GCP (preferred, but flexible depending on experience)
*LLMs / GenAI / RAG / agentic frameworks (LangChain, LlamaIndex etc.)
*MLOps tools: Git, CI/CD, Docker, Kubernetes, APIs
What you bringCore requirements*5+ years in data science / machine learning
*Strong foundation in traditional ML (e.g. XGBoost, regression, statistical modelling)
*Hands-on experience with LLMs / GenAI / NLP / AI systems
*Experience deploying models into production (not just experimentation)
*Familiarity with MLOps, CI/CD, and containerisation
*Strong stakeholder skills - comfortable working with department heads and leading projects
Nice to have*Experience in regulated industries (insurance, finance, etc.)
*Customer-focused product experience
*Strong academic background in a quantitative field
*Exposure to building agentic workflows or RAG systems in production
Why this role*Work on real AI products, not just experimentation
*End-to-end ownership across modelling, deployment, and impact
*Exposure to cutting-edge GenAI and agentic systems
*Highly collaborative, cross-functional environment
*Strong visibility across the business
Interview process*30-minute culture fit interview
*Technical interview (solution design + deployment / ML discussion)
*Final interview with senior leadership (CDO)
Working style*2 days per week in London (flexible for Midlands candidates)
*Ideally Tues/Weds in office
*Cross-functional, collaborative environment with strong stakeholder interaction