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    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.

    Consultant

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