Data Scientist (Football Club)

Job DescriptionThis is a unique opportunity to work at the cutting edge of AI, data technology, and elite football analytics. As a Data Scientist, you'll join a collaborative, high-performing team with a culture rooted in creativity, innovation, and excellence. In this role, you'll design and deploy data models that power decision-making across every area of the club - from strategy, tactics, recruitment, and performance, to pre- and post-match analysis. You'll also play a key role in supporting the club's commercial operations, including e-commerce and fan engagement. If you're passionate about using advanced data science to drive real-world impact in sport, this is the role for you., Develop and apply statistical models and algorithms to analyse player performance, match outcomes, and tactical insightsCollect, clean, and process football-related data from diverse sourcesBuild clear, compelling visualizations and deliver insights to both technical and non-technical stakeholdersCollaborate with analysts, coaches, and performance staff to understand requirements and translate them into actionable data solutionsStay up to date with advancements in sports analytics, machine learning, and data science methodologies

3+ years of industry experience as a Data Scientist, plus a strong academic foundationPython Data Science Stack: Advanced proficiency in Python, including Pandas, NumPy and scikit-learn.Statistical & Machine Learning Modelling: Experience with a variety of ML techniques (regression, classification, clustering, time-series forecasting)Experience with deep learning frameworks such as Keras or PyTorchModel Deployment: Proven ability to productionise models, including building and deploying APIsStrong visualization and communication skills, with the ability to translate complex technical findings into actionable insights for coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience: Familiarity with football-specific datasets (event, tracking, positional), and libraries like mplsoccerAdvanced MLOps & Modelling: Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation, tactical modelling, etc.Bayesian Modelling: Knowledge of probabilistic programming (e.g., PyMC) for uncertainty-aware predictionsStakeholder Collaboration: Demonstrated ability to work directly with stakeholders to scope, iterate, and deliver impactful solutions in fast-moving environments What They Offer A chance to work on real-world data that impacts elite football performanceAccess to high-value datasets, sports science teams, and cross-disciplinary expertsA flexible hybrid working model (1 day per month in the London office)The opportunity to grow within a digital-first team at a world-renowned football clubThe satisfaction of applying your engineering skills in an environment where your work directly influences results on the pitch