Football Data Scientist — AI & Player Analytics

saintsfc; Southampton; On-site; GBP 65,000 - 90,000; Full time

Benefits offered by this job

2 free match tickets

Staff health & wellbeing initiatives

Merchandise discount

25 days' holiday + birthday off

Pension scheme

Worldwide travel insurance

Learning & development

Free onsite parking

Cycle to Work Scheme

Inclusive working culture

Job summary

Southampton FC (SFC) is seeking a Data Scientist based at Staplewood Training Ground to deliver insights across recruitment, performance analysis, sports science, and player development.

You'll build automated data pipelines and predictive models, collaborate with data engineers, and present findings to coaches and staff at multiple clubs within the group. Experience with R/Python and BI tools is preferred.

Qualifications

• Requires an undergraduate degree (or postgraduate desirable) in Mathematics, Statistics, Computer Science or related STEM field.
• Experience building statistical models and/or ML algorithms; strong programming in R or Python.

Responsibilities

• Maintain and develop automated data pipelines to process data and create metrics.
• Build advanced predictive models to measure and classify player and team performance.
• Collaborate with data engineers on data cleansing and ingestion for databases.
• Present and explain findings to stakeholders across clubs and audiences.

Skills

Data pipelines

Predictive models

R or Python

Power BI

Tableau

Data visualization

Communication

Multilingual ability

Education

Bachelor's degree in Mathematics/Statistics/CS

Tools

Power BI

Tableau

Job description

Southampton FC (SFC) is seeking a Data Scientist based at Staplewood Training Ground to deliver insights across recruitment, performance analysis, sports science, and player development.

You'll build automated data pipelines and predictive models, collaborate with data engineers, and present findings to coaches and staff at multiple clubs within the group. Experience with R/Python and BI tools is preferred.