Data Scientist

BettingJobs is currently hiring for a Data Scientist based in London for a leading sports betting services company.

Responsibilities:

• Design, build, and maintain statistical or machine learning models to support sports 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 analysis (EDA), feature engineering, and model evaluation to support continuous model improvement.
• Write clean, efficient, well-documented code aligned with team standards for structure, reproducibility, and version control.
• Work collaboratively with other Data Scientists to propose ideas, troubleshoot modelling challenges, and refine methodologies.
• Contribute to the delivery of accurate, reliable forecasts with low latency under evolving client or market demands.
• Participate in code reviews and collaborative design sessions to uphold technical quality across the team.
• Provide mentorship and support to Junior Data Scientists working on the same or related projects.

Requirements:

• A degree (PhD, MSc, BSc) in a STEM subject or similar provable numerate and quantitative skills.
• 2+ years’ experience solving analytics and modelling problems, ideally in sport, gaming, or similar domains with forecasting needs.
• 2+ years working with Python or R in a production or research setting.
• Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr).
• Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow.
• Experience working with SQL and relational databases.
• Ability to explain model behaviour through visualisations and reports.
• Familiarity with Git and collaborative development workflows.
• Good written and verbal communication; able to contribute to cross-functional discussions.
• Proven problem-solving and time management skills.