Hybrid Football Data Scientist - R&D & ML Modelling

The Football Association; Burton upon Trent; Híbrido; GBP 65.000 - 90.000; Tempo integral

Benefícios oferecidos por esta vaga

Private medical cover funded by The FA

Pension plan

Gen tickets & events

Resumo da vaga

The Football Association (The FA) is recruiting a Research & Development Data Scientist to design and build world-class statistical and ML models that provide a competitive edge to England teams. You will develop novel methodologies using event, tracking, GPS, and performance data, and translate findings into actionable insights for stakeholders.

You will work across data science, data engineering, and visualization to deliver robust models and dashboards, with a focus on rigour, documentation,

Qualificações

• Master's degree in a highly quantitative field (maths/statistics/CS).
• Strong grounding in statistics and machine learning methodologies.
• Experience with real-world data to derive actionable insights.
• Proficiency in Python and related data-science tooling.
• Ability to work with football datasets and communicate results to stakeholders.

Responsabilidades

• Design and implement world-leading statistical and machine learning models for football data.
• Develop data-driven insights to support England teams.
• Collaborate with Data Engineering to integrate analytics outputs.
• Create compelling visualisations and deploy them in web apps.
• Ensure model validation and monitoring over time.

Conhecimentos

Statistical modeling

Python

Communication

ML/AI concepts

Formação

Master's degree in mathematics/statistics/computer science

Ferramentas

Python

Google Cloud Platform

GitHub

Descrição da vaga

The Football Association (The FA) is recruiting a Research & Development Data Scientist to design and build world-class statistical and ML models that provide a competitive edge to England teams. You will develop novel methodologies using event, tracking, GPS, and performance data, and translate findings into actionable insights for stakeholders.

You will work across data science, data engineering, and visualization to deliver robust models and dashboards, with a focus on rigour, documentation,