Data Scientist (Football Club)

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