What you'll do
You will work within a small, highly technical team responsible for developing and scaling computer vision-driven analytics , while collaborating closely with consulting teams that translate insights into strategic recommendations for clients.
What you’ll be working on
- Developing and improving computer vision models used to analyse sports broadcast footage
- Detecting and tracking brand exposure, sponsorship assets and on-screen visibility
- Working with large datasets and video/image pipelines to generate commercial insights
- Writing Python scripts and data workflows to support analysis and automation
- Extracting and managing data using SQL
- Supporting the transition from legacy analysis workflows to new automated CV-driven systems
- Contributing to insights that support sponsorship valuation and media analytics projects
Tech & tools
- Python
- SQL
- Computer vision / machine learning models
- Image and video analysis workflows
About the role
Initially this is a technical, hands-on data science role , focused on building and scaling computer vision analytics.
Over time, there is the opportunity to become more involved in client-facing consulting projects , helping translate technical outputs into commercial insights for stakeholders across the global sports industry.
What we’re looking for
- Experience with Python and SQL
- Exposure to computer vision or image/video analysis
- Strong analytical thinking and problem-solving ability
- Interest in applying data science to real-world commercial challenges
- A genuine interest in sport and the sports business industry
Experience level
We are open to candidates at Analyst or Senior Analyst level , typically with 2–4 years of relevant experience in areas such as:
- Data science
- Machine learning
- Computer vision
- Analytics engineering
- Sports analytics
- Data consulting
This is a rare opportunity to apply cutting-edge computer vision technology to some of the most recognisable brands, leagues and sponsorship programmes in global sport.
If you’d like to learn more, apply!
Vacancy posted more than 2 months ago
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