Data Scientist

Sports Data Scientist (Football)

Remote

€425 per day – based on a 40-hour working week

12-Month Contract

We are seeking an experienced Sports Data Scientist with a strong focus on football analytics to join a high-impact, data-driven performance project. This is a 12-month remote contract, offering €425 per day.

This role will focus on large-scale football data analysis, integrating advanced datasets to generate actionable performance insights and support innovation across performance and product development.

The Role

You will work on advanced football analytics projects, applying data science and machine learning techniques to uncover tactical, technical, and performance-driven insights from elite-level match data.

The role combines analytical modelling, feature engineering, and data integration across multiple football datasets, including event and tracking data.

Key Responsibilities

• Develop and implement advanced analytics models in Python and/or R
• Analyse large-scale football event and performance datasets
• Identify key performance drivers (e.g. passing, shooting, dribbling, ball progression)
• Apply machine learning techniques such as clustering, feature engineering, and predictive modelling
• Generate insights into tactical patterns and performance trends
• Validate and integrate multiple football data sources
• Translate analytical outputs into actionable insights for performance and product stakeholders
• Contribute to scalable data pipeline and modelling frameworks

Required Experience

• Strong experience as a Data Scientist, ideally within sport or football analytics
• Advanced proficiency in Python (pandas, scikit-learn, numpy) and/or R
• Experience working with large, complex datasets
• Experience working with the sports data tool Statsbomb
• Strong understanding of statistical modelling and machine learning
• Experience analysing football event or tracking data (e.g. passes, shots, ball movement)
• Ability to communicate technical insights clearly to non-technical stakeholders

Desirable

• Experience with professional or elite-level football data
• Experience with data engineering concepts and pipeline development
• Background in performance analysis or sports science
• Experience working in remote, cross-functional environments