Data Scientist (Football Club)
Role details
Job location
Tech stack
Job description
provide actionable insights.Stay updated with the latest trends and advancements in sports analytics and data science.What you'll bring3+ years industry experience in a Data Science role and a strong academic backgroundPython Data Science Stack: Advanced proficiency in Python, including Pandas, NumPy, scikit-learn, and Jupyter Notebooks.Statistical & ML Modelling: Strong foundation in statistical analysis and experience applying machine learning techniques (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required.Full-Stack Deployment: Experience taking models to production, including building and deploying APIs.Visualization & Communication: Ability to create clear visualizations and effectively communicate technical findings to non-technical stakeholders.Highly desirable skillsFootball Analytics Domain: Experience with football datasets (event, tracking, etc.) and visualization libraries like mplsoccer.Advanced
Requirements
MLOps & Modelling: Experience with Vertex AI lifecycle (especially Pipelines) and modelling techniques relevant to football (e.g., player valuation, tactical analysis).Bayesian Modelling: Experience with probabilistic programming (e.g., PyMC).Stakeholder Management: Proven success working directly with business stakeholders to define and deliver impactful solutions.What They OfferWork that impacts elite football performance and club-wide successAccess to real-world sports data and performance analyticsFlexible working options (hybrid/remote depending on role)Opportunity to grow with a digital-first team inside a world-renowned clubSeniority levelMid-Senior levelEmployment typeFull-timeJob functionSoftware DevelopmentLondon, England, United Kingdom #J-18808-Ljbffr