Overview
We have a fantastic new opportunity to join our team at Smartodds as a Club Football Quantitative Analyst. Based in North London, Smartodds provides in-depth research and analysis on sporting events around the world, supported by world-class, bespoke software platforms. We are proud of our collaborative and dynamic culture, grounded in our core values of Boldness, Open-mindedness, Ownership, and Togetherness. We are a supportive and collaborative team – our environment is open, inclusive, and focused on doing great work together.
While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required.
About the role As a member of the Quant Team, you will join an exciting environment predicting outcomes of professional sports on behalf of our clients. We focus on football, baseball, basketball, cricket, tennis, American football, ice hockey, horseracing and golf. In this role, you will join our newly created ClubFootball team – a specialised sub-team within the Quant Team – developing statistical models exclusively for football. You will work closely with our partner clubs, including Brentford FC and Mérida AD, to improve performance through two core areas:
- In-game strategy optimisation
- Ratings players for the purpose of recruitment and development
This role combines rigorous statistical modelling with production engineering. You will take models from research through to deployment, writing well-tested, documented code that integrates into our internal libraries. The atmosphere is collaborative and includes academic-peer reviews, research talks, and further education opportunities—but unlike academia, the market and club performance provide immediate feedback on model quality. This makes the job challenging but also very exciting.
You will have plenty of autonomy to execute your models from idea to code to validation to (hopefully) deployment. xwzovoh However, this autonomy operates within a structured framework: established coding patterns, weekly check-ins, high test coverage, and strict reproducibility standards.
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