About the Role

Join our Sportsbook team as a Graduate Data Scientist / Trader, where you'll gain hands-on experience working at the intersection of quantitative modeling and trading operations. You'll help support the development and monitoring of predictive models that power real-time odds and trading decisions, while also participating in trading workflows for pre-match and in-play sports betting markets.

This is an excellent opportunity for an analytically minded graduate with a passion for sports, data, and betting markets to learn from an experienced team and grow into a hybrid quant/trading role.

 

Key Responsibilities

Assist in building, testing, and maintaining statistical models used to price sportsbook markets (e.g., moneyline, spreads, totals, props). Conduct exploratory data analysis and feature engineering using historical sports data and real-time feeds. Analyze performance metrics like margin, P&L, and customer behavior to improve pricing accuracy and model calibration. Work closely with Trading, Product, and Engineering teams to support model improvements and ensure seamless trading execution.. Stay up-to-date with sports analytics, statistical methods, and advanced machine learning; evaluate new methods to keep our models best-in-class. Support traders with pricing, risk management, and market monitoring during live events. Monitor odds movement, betting patterns, and liabilities to help ensure market efficiency. Contribute to setting pre-match and in-play prices using internal tools and models.

Qualifications

Bachelor’s or Master’s degree in a quantitative field such as Statistics, Mathematics, Computer Science, Engineering, or similar. Solid foundation in probability and statistics, with an interest in applying these to real-world problems. Strong programming skills in Python (especially with data-focused libraries like pandas and NumPy). Passion for sports and interest in sportsbook mechanics or financial markets. Strong attention to detail, especially when working with live data and pricing environments. Willingness to work flexible hours during major sporting events as needed.

Nice to Have

Familiarity with sports betting odds and common market types (e.g., spread, totals, player props). Exposure to sports analytics or participation in data competitions (e.g., Kaggle, university research). Experience with data visualization tools or dashboarding Prior experience in a sportsbook, trading desk, or similar high-tempo environment.