Sports Data Science Jobs

Data science roles in sport go beyond traditional analytics — they typically involve machine learning, statistical modelling, and large-scale data infrastructure. You might be building a player recruitment model that scores thousands of prospects, or developing a real-time decision support tool for in-game coaching decisions.

Sports data science positions often sit within a club's football or sports operations department, or within the commercial analytics team. The technical bar is high — most roles expect proficiency in Python or R, experience with machine learning frameworks, and the ability to work with large datasets from sources such as tracking providers, video platforms, and internal club databases.

It's one of the most technically demanding areas of sports employment, but also one of the most rewarding. See the newest sports data science roles below.