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Senior data scientist

London
Burns Sheehan
Data scientist
Posted: 1 January
Offer description

Senior Data Scientist Remote (UK) | Occasional Travel to London | Full-Time Salary: up to £95,000We’re working with a business who are building an AI-powered platform that helps brands activate their happiest customers through intelligent referral journeys, reward automation, and predictive modelling. As we expand our generative AI and experimentation capabilities, we’re hiring a full-stack Senior Data Scientist who loves solving ambiguous problems, prototyping fast, and turning data into meaningful product experiences. What You’ll Work OnIn this role, you’ll be hands-on across the full data science lifecycle—from idea to prototype to production. If you enjoy wearing multiple hats and working in fast-moving, high-growth environments, you’ll thrive here.You’ll work on projects such as:Prototyping generative AI applications and scalable LLM-powered toolsDesigning and running experiments and A/B tests to validate new ideasConducting consumer behaviour and segmentation researchDeveloping causal models to understand the drivers of customer advocacy and business growthBuilding “imperfect,” rapid prototypes to explore product-market fitThis is a Senior IC role—ideal for someone who wants to stay hands-on and move fast. What We’re Looking ForWe’re looking for a generalist, not a narrow specialist—someone comfortable with modelling, experimentation, prototyping, and cross-functional collaboration.You’re a great fit if you:Have strong experience with ML and generative AI/LLM developmentLove rapid experimentation and hypothesis-driven prototypingAre comfortable operating in uncertainty and evolving problem spacesHave startup, scaleup, or high-growth experienceCan manage multiple projects and context-switch easilyCommunicate clearly with both technical and non-technical audiencesBring an entrepreneurial mindset and enjoy turning data into product valueNice to have:E-commerce or consumer behaviour experience (e.g., rapid growth environments)Familiarity with GANs, VAEs, causal inference, or rapid prototyping frameworksNon-linear or multidisciplinary career paths

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