9 of 9 Remote/Hybrid Experimental Design Jobs in the UK

growth models, recommendation systems, gradient boosting & ensemble methods, NLP/text analytics, time-series forecasting, & generative AI use cases Monitor model performance and design experiments tied to clear hypotheses Translate ambiguous business questions into measurable, actionable solutions Coach and mentor junior data scientists, raising the bar on technical ...

wider enterprise, working across multidisciplinary teams throughout the UK. You will collaborate with delivery managers, engineers, architects, and customer stakeholders to design, develop, and operationalise data‐driven solutions that deliver meaningful impact. This role offers the opportunity to deepen your expertise, contribute to high‐value projects, and help … libraries (pandas, NumPy, scikit‐learn, TensorFlow, PyTorch) Experience designing, training, and evaluating machine‐learning models Solid understanding of statistical methods, predictive modelling, and experimental design Experience working with large or complex datasets, including data cleansing and feature engineering Ability to communicate analytical concepts clearly to non‐technical ...

cloud services (SageMaker, Lambda, S3) Familiarity with MLOps tools (MLflow, Weights & Biases) Knowledge of NLP, computer vision, or time-series analysis Ability to design experiments and apply statistical validation Understanding of Responsible AI principles and model explainability Ready to take your data science expertise to the next level ...

opportunities, improve customer experiences, and drive measurable impact. Key Responsibilities: Analyse user behaviour to uncover insights, identify pain points, and influence product direction. Design experiments and support a culture of testing, learning, and iteration. Define and align key business metrics, ensuring consistency and accuracy across teams. Build ...

opportunities, improve customer experiences, and drive measurable impact. Key Responsibilities: Analyse user behaviour to uncover insights, identify pain points, and influence product direction. Design experiments and support a culture of testing, learning, and iteration. Define and align key business metrics, ensuring consistency and accuracy across teams. Build ...

user behaviour and product performance across key journeys Build dashboards and self-serve insights for cross-functional teams Support A/B testing: design experiments, interpret results, recommend next steps Work with data and platform teams to ensure clean, scalable datasets Present clear, actionable insights that influence product ...

client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback (RLHF) and Generative AI. In this role, you will design and optimise the algorithms that align large-scale generative models with human preferences, ensuring they are safe, controllable, and capable of producing high-quality outputs … learning methods (policy gradients, actor-critic, off-policy learning) for model alignment. Train, fine-tune, and evaluate LLMs and diffusion models at scale. Design experiments to align generative outputs with human and organisational preferences. Collaborate with researchers, engineers, and human feedback teams to build scalable alignment pipelines. Publish ...

shape product decisions, live ops strategies, and player experiences. Reporting to the Senior Data Growth Manager, you’ll own key metrics, build forecasts, design experiments, and inform growth strategies through rigorous analysis. With a strong grasp of player behaviour and an appetite to learn … passionate users. WHAT YOU’LL DO Own and analyse core KPIs across our mobile games — including retention, monetisation, engagement, and player sentiment Design and evaluate experiments across new features, live ops, content releases, and monetisation strategies Build dashboards and models that support performance tracking, forecasting, and opportunity sizing ...

transform, and analyse large order/delivery datasets; build visualisations and executive-ready summaries (vehicle utilisation, mileage, cost, quantities, OTR). Parameter tuning: Design experiments, sweep parameters, evaluate trade-offs, and recommend configurations (e.g., slot windows, min-qty thresholds, SKU segregation). API usage & integration: Read docs, consume … Command services). Interview process 30-min intro (role, your goals) Python data task (clean/transform + quick viz) API & systems chat (design a small data pull + retries/observability) Simulation case (parameter trade-offs; short write-up) Stakeholder round (present findings; Q&A) What ...