Data Scientist (Football Club)
5 days ago
City of London
This 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. Key Responsibilities • Develop and apply statistical models and algorithms to analyse player performance, match outcomes, and tactical insights, • Collect, clean, and process football-related data from diverse sources, • Build clear, compelling visualizations and deliver insights to both technical and non-technical stakeholders, • Collaborate with analysts, coaches, and performance staff to understand requirements and translate them into actionable data solutions, • Stay up to date with advancements in sports analytics, machine learning, and data science methodologies Your Background • 3+ years of industry experience as a Data Scientist, plus a strong academic foundation, • Python 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 PyTorch, • Model Deployment: Proven ability to productionise models, including building and deploying APIs, • Strong 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 mplsoccer, • Advanced 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 predictions, • Stakeholder 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 performance, • Access to high-value datasets, sports science teams, and cross-disciplinary experts, • A 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 club, • The satisfaction of applying your engineering skills in an environment where your work directly influences results on the pitch