Data Scientists (All Levels) - UK Wide

We work with a range of UK employers actively hiring across these roles. Job Description: UK-Based (On-Site, Hybrid or Remote) About the Roles We're looking for talented Data Scientists at all levels—from Data Scientist through to Senior, Lead and Principal, and spanning Applied Scientist, Research Scientist, Decision Scientist and Product Data Scientist—for upcoming roles where data science genuinely drives decisions. These are roles focused on insight, experimentation and modelling: turning messy real-world data into the understanding and predictions that change what a business does next. You'll work across the full data science lifecycle—from framing the problem and exploring the data through to modelling, experimentation, communication and measuring impact. The role suits someone who pairs strong statistical and modelling rigour with genuine curiosity about the problem and the storytelling skill to make a result land with the people who'll act on it. Key Responsibilities • Frame business questions as tractable data science and experimentation problems • Conduct exploratory analysis, statistical modelling and hypothesis testing • Build predictive and inferential models that drive real decisions • Design and analyse experiments—A/B testing and causal inference • Apply machine learning where it's the right tool, with a focus on insight and impact • Communicate findings and recommendations clearly to technical and non-technical audiences • Partner with ML engineers to productionise models that need to ship and scale • Develop metrics and measurement frameworks that help teams make better decisions • (For Senior / Lead roles) Set standards, mentor scientists and lead cross-functional initiatives What You'll Bring Technical Expertise: • Strong Python (pandas, scikit-learn, statsmodels) and / or R • Solid statistics—inference, experimental design and causal methods • Machine learning—supervised and unsupervised methods and rigorous evaluation • Strong SQL and comfort with messy, real-world data • Experimentation and A/B testing, and causal inference techniques • Cloud and notebook environments; exposure to ML frameworks (PyTorch, TensorFlow) is a plus • Awareness of LLMs and generative AI for applied use cases A note on scope: this lane is about insight, experimentation and modelling. If your focus is productionising, serving and operating models at scale, our AI / ML Engineer roles are likely the better fit—and we're hiring across both. Analytical & Soft Skills: • Genuine curiosity about the problem behind the data • Rigour in methodology, validation and reproducibility • Excellent communication and data storytelling • Strong business sense—connecting analysis to decisions and outcomes • Comfortable with ambiguity and shaping unclear questions into structured work • Collaborative approach across product, engineering and commercial teams Domain Flexibility: • Roles span product, marketing, customer, risk, operations and research across SaaS, fintech, retail, healthcare, media and public sector • Background in any of these is welcomed; appetite to learn an adjacent domain valued just as much Experience Level: • Minimum 2+ years for Data Scientist, 5+ for Senior, 8+ for Lead / Principal • Background in data science, applied science, research science or decision science • Examples of models, experiments or analyses you've owned end-to-end and the decisions they shaped What We Offer • The opportunity to work where data science genuinely drives decisions, not just dashboards • Exposure to modern data science tooling, experimentation platforms and ML frameworks • Roles at the level you're ready for—we're hiring across the full data science spectrum • A collaborative environment where statistical rigour and clear communication are both valued • Clear scope to develop specialist depth (causal, product, research, applied ML) or stay broad • Flexible working arrangements (on-site, hybrid or remote) and supportive team culture