Careers

Could you build the future of football?

Three career pathways, including what people actually do and what they need to learn — plus every route in, with or without university.

Find your path

Which part of artificial intelligence in football interests you?

Pick the one that sounds most like you.

01 / PATHWAY

Computer Vision Engineer

Teach computers to see and understand the world.

In footballTracking every player and the ball from match footage, then turning it into positions, distances and highlights automatically.
Explore this pathway →

What you'd actually do

  • Collect and label images and video
  • Train models to detect and track objects
  • Test how accurate they are, and improve them
  • Make models fast enough to run on real footage

What to learn

  • Python programming
  • Maths: linear algebra and probability
  • Machine learning and deep learning
  • Tools like OpenCV and PyTorch
02 / PATHWAY

Data Scientist

Find patterns and insights hidden in data.

In footballFinding players with a similar style to a target signing, or spotting which training loads lead to injuries.
Explore this pathway →

What you'd actually do

  • Gather and clean messy data
  • Explore it to find trends and patterns
  • Build models that make predictions
  • Explain findings with clear charts and stories

What to learn

  • Python or R, plus SQL
  • Statistics and probability
  • Machine learning basics
  • Data visualisation and communication
03 / PATHWAY

Technology Entrepreneur

Turn an idea into something people actually use.

In footballSpotting that grassroots teams have no access to match analysis, and building an affordable product that gives it to them.
Explore this pathway →

What you'd actually do

  • Find a real problem worth solving
  • Talk to the people who have it
  • Build a simple first version and test it
  • Grow a team, a product and a business

What to learn

  • Enough coding to build a prototype
  • Product thinking and user research
  • Business basics: customers, pricing, money
  • Pitching, persuasion and resilience
Routes in

You don't have to go to university to work in artificial intelligence

There's more than one way in. Each route has its strengths and trade-offs — the right one depends on you.

University degree

  • Deep theory, credibility with employers and wide career options
  • Costly, and less hands-on unless you do a placement year
Studying Computer Science →

Degree apprenticeship

  • Earn a degree and a salary, pay no tuition fees, and get real experience
  • Competitive, with less choice of employer

Self-teaching and building projects

  • Free, flexible, and you build what you love
  • No structure, and harder to get hired without a portfolio
How to build a portfolio →

Coding bootcamps and structured courses

  • Fast, focused and practical, with a clear structure
  • Can be expensive, quality varies, and they cover less theory

Starting a business

  • You learn everything by doing, and build something you believe in
  • Risky, with no guaranteed income
How I built GoalPro →

Thinking about a CS degree?

What it gives you, what it doesn't, what the course is like, and how to use it to get into football data.

Is a CS degree enough? →
Whichever route you pick, build things alongside it.CS gave me the foundation. Teaching myself computer vision got GoalPro built.
Where to start

You don't need to know where to start — just be curious.

Pick a part of football you love, find a question you want answered, and try to answer it with a little code and some data. Every one of these careers begins with a small project.

See projects for inspiration ↗