Remote Data Scientist - Football Analytics & ML Innovation

The Football Association; England; Hybrid; GBP 70,000 - 95,000; Full time

Benefits offered by this job

Free lunches

Private medical cover

Contributory pension

25 days annual leave

Hybrid working model

Event day tickets

Job summary

The Football Association is recruiting a Research & Development Data Scientist to design and build world-leading statistical and machine learning models for English football. You will develop methodologies using event data, tracking data, and GPS/performance data, delivering insights to a wide range of stakeholders.

You will work across data science research, data engineering, and data visualization, ensuring models are well-documented, validated, and embedded in decision-making.

Qualifications

• Master's degree in a highly quantitative field; PhD desirable but not essential.
• Strong theoretical grounding in statistics and ML, with ability to engage with methodology behind advanced data science.
• Experience with football datasets (e.g. event or tracking data) desirable but not essential.
• Proficiency in Python for statistical modelling.
• Ability to be physically present at St. George's Park.
• Excellent written and verbal communication skills.

Responsibilities

• Design and implement world-leading statistical and ML models for football data.
• Develop data pipelines and integrate analytics reporting with models.
• Translate complex model outputs into actionable insights via visualization and dashboards.
• Collaborate with stakeholders to deploy visualisations and web app outputs.
• Support other analytics tasks and adhere to rigorous validation standards.

Skills

Statistical modelling

Python

Data visualization

Stakeholder communication

Education

Master's degree in mathematics/statistics/computer science

PhD desirable

Tools

Google Cloud Platform

GitHub

React

Job description

The Football Association is recruiting a Research & Development Data Scientist to design and build world-leading statistical and machine learning models for English football. You will develop methodologies using event data, tracking data, and GPS/performance data, delivering insights to a wide range of stakeholders.

You will work across data science research, data engineering, and data visualization, ensuring models are well-documented, validated, and embedded in decision-making.