2 of 2 Remote Data Munging Jobs in the Thames Valley

Data Scientist Salary: £55-70k plus attractive bonus on top Location: London or Leeds (hybrid working, if preferred) About us We have an exciting opportunity for a Data Scientist to join our rapidly growing Sports Forecasting & Analytics company. Purpose of the role As a Data Scientist within the Modelling & Data Engineering … ensure our forecasts remain accurate, low-latency, and aligned with client demands. You will be expected to use your programming, analytical, and mathematical skills to extract insights from data, build high-performance modelling pipelines, and help improve modelling practices across the business. This role is ideal for someone with a strong foundation in data science who … forecasting and pricing across various markets. Extract actionable insights from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements and business objectives into effective data science solutions, working closely with the Delivery Manager and Engineering teammates (Software and Data Engineers) within your modelling team. Perform data cleaning, exploratory data More ❯

Junior Data Scientist – Master’s Graduate Role Location: London (Hybrid) Salary: £40,000 – £45,000 + Bonus + Benefits Start Date: ASAP About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and … apply their academic expertise to solving real-world challenges—whether it’s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing … and building machine learning models to solve real-world problems Carrying out full data science workflows: from data acquisition and cleaning to modelling, validation, and deployment Applying statistical and AI techniques to generate actionable insights Contributing to experimental research, model prototyping, and A/B testing Presenting findings clearly to both technical and non-technical stakeholders More ❯