About the Opportunity
This is a rare opportunity for a Data Scientist to work at the intersection of cutting-edge technology and elite sports performance. You’ll join a collaborative, high-standard engineering team with a culture built around creativity, innovation, and excellence.
In this role, you’ll play a key part in designing and developing scalable data models that directly impacts decision-making at the highest levels of the football world—including performance insights for some of the most well-known footballers in the industry.
This is the perfect environment for those passionate about leveraging advanced data engineering to drive real-world results in sports analytics.
Key Responsibilities
* Collect, clean, and process football-related data from diverse sources
* Develop and apply statistical models and machine learning algorithms to analyse player performance, match outcomes, and tactical insights
* 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, scikit-learn, and Jupyter Notebooks
* 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
* Work that directly impacts elite football performance and club-wide decision-making
* Access to real-world sports data, high-performance environments, and cutting-edge tools
* A digital-first, flexible working environment (remote or hybrid depending on role)
* The opportunity to grow and shape your career inside a globally recognised football institution