Football Analytics R&D Data Scientist (Hybrid)

Comunidadlift; Burton upon Trent; On-site; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Event day tickets at Wembley Stadium

Free lunches at Wembley Stadium and St

Private medical cover

Contributory pension

25 days annual leave

Hybrid working model

Job summary

The FA is seeking a Research & Development Data Scientist to design and build state-of-the-art statistical and ML models for England teams. You will translate complex outputs into actionable insights for a wide range of stakeholders and embed data-driven decisions across football operations.

You will work across data science, engineering and visualization, build robust pipelines, and push methodological boundaries while ensuring rigorous validation and documentation.

Qualifications

• Master’s in a highly quantitative field; PhD desirable but not essential.
• Strong grounding in statistics and ML with ability to critique literature.
• Practical data science experience with real-world data and football datasets.

Responsibilities

• Design and implement world-leading statistical and ML models.
• Collaborate with stakeholders to translate outputs into insights.
• Develop data visualisations and deploy them in web apps.
• Document model development and ensure rigour and validation.
• Engage with data engineering to integrate analytics pipelines.

Skills

Statistical modelling

ML & AI theory

Data science practice

Python programming

Communication skills

Education

Master's degree (math/statistics/computer science)

PhD desirable

Tools

Google Cloud Platform

GitHub

React

Job description

The FA is seeking a Research & Development Data Scientist to design and build state-of-the-art statistical and ML models for England teams. You will translate complex outputs into actionable insights for a wide range of stakeholders and embed data-driven decisions across football operations.

You will work across data science, engineering and visualization, build robust pipelines, and push methodological boundaries while ensuring rigorous validation and documentation.