Contract Data Scientist - Forecasting, Deep Learning, Causal AI (Retail) £600-700/day | 4 Months | Start ASAP | Inside IR35 RAPP is looking for a technically sharp, hands-on Data Scientist to join their agile consulting team supporting high-profile retail clients. This is a 4-month contract with the chance to work on impactful forecasting and causal AI projects within a fast-moving, agency-style environment. What You'll Be Doing: • Designing and building custom forecasting models (XGBoost, deep learning, RL) for real-world retail scenarios • Applying causal and graph-based methods to understand and optimise customer behaviour • Working across the full stack of data science, from data wrangling to deployment • Operating within a modern MLOps setup (Docker, CI/CD, AWS) • Contributing to product-facing tooling (bonus if you've used JavaScript / Next.js / TypeScript) What We're Looking For: • Strong practical knowledge of deep learning fundamentals - ideally with PyTorch • Experience building bespoke models for time series, tabular, image, or text data • Hands-on forecasting experience with retail or consumer datasets • Skilled in causal inference, graph AI, or reinforcement learning • Comfortable deploying models in production environments • Strong communicator, able to clearly explain technical choices and trade-offs Nice to Have: • Exposure to JavaScript, TypeScript, or Next.js • Prior work in a startup, agency, or consultancy environment This is a fast-paced project with immediate impact - if you're a data scientist who thrives on building models from scratch and solving tough commercial problems, this one's for you. Desired Skills and Experience Python, PyTorch, XGBoost, Deep Learning, Forecasting, Causal AI, Graph AI, Reinforcement Learning, Time Series, AWS, Docker, CI/CD