Senior Data Scientist

• Enjoys tackling hard, open-ended problems and seeing the solution through to real users
• Has a get-things-done mindset and takes work from idea to delivery
• Keeps learning and stays current in a fast-moving field
• Practical and collaborative: argues a position with conviction, and changes it when the evidence says so
• Explains technical ideas clearly to engineers and commercial teams alike
• Works independently and manages their own time and priorities well

You’ll be responsible for

• Designing, building and shipping LLM and agent-based systems, from first prototype to live product
• Building retrieval pipelines (RAG, ranking, recommendation, summarisation, grounded Q&A)
• Training, fine-tuning and optimising models, mainly for language tasks
• Defining how we measure success, through offline evals, experiments and production monitoring tied to user and commercial outcomes
• Keeping systems dependable, with automated testing, observability, troubleshooting and incident response
• Setting the bar for code quality, security, data governance and documentation
• Working closely with engineering, data and product teams, and mentoring others

Strong ML experience, hands-on NLP and production experience with agentic AI are essential. Our stack includes AWS, Python, PyTorch, Docker, LangChain/LangGraph and Langfuse. Experience with reinforcement learning or an understanding of sales psychology would be desirable plus there’s plenty of ambitious work now and upcoming., * Extensive experience in data science and ML, including hands-on delivery of LLM-powered and agentic systems running in production at scale

• Works AI-natively day to day, using AI tools and agents as a core part of how they build, test and ship
• Strong Python, plus PyTorch, scikit-learn or similar frameworks
• Hands-on LLM work: prompting, fine-tuning, grounding and guardrails
• Agentic systems at scale, including orchestration (LangChain/LangGraph), tracing and evals (Langfuse), memory design, and latency and cost trade-offs
• Embeddings, vector search and hybrid search
• Solid grounding in statistics and ML theory across supervised and unsupervised learning, NLP (entities, intent), recommendation, prediction and uplift modelling
• Full model lifecycle and MLOps: containerisation (Docker/ECR) and deployment on AWS
• Working with large text datasets and data pipelines
• Nice to have: sales psychology applied in data products

Please note that this is a hybrid role and will require regular travel to our Brighton office.

• Medicash healthcare scheme (reclaim costs for dental, physiotherapy, osteopathy and optical care)
• Private Medical Insurance via AXA (after 1 year service) Launching in April 2026
• Life Insurance scheme
• 25 days holiday + bank holidays + your birthday off (rising to 28 after 3 consecutive years with the business & 30 after 5 years). Including Christmas closures.
• Employee Assistance Programme (confidential counselling)
• Gogeta nursery salary sacrifice scheme (save up to 40% per year)
• Enhanced parental leave and pay including 26 weeks’ full maternity pay and 8 weeks’ paternity leave