At Football Radar, our mission is to be the world-leading provider of football analytics. For over a decade, we have combined predictive modelling techniques with expert analysis and our proprietary datasets to deliver insights that drive success for our betting clients and football clubs. By combining the agility of a start-up with the stability of an established business, we’ve created an environment where innovation and long-term success go hand in hand.
About The Role
As a Quantitative Analyst on our prediction team, you will use our extensive dataset to enhance existing predictive models, research new methods, and turn your insights into production-ready solutions. This research will involve a mix of well-executed analyses and innovative modelling to solve unique challenges in football analytics, where traditional methods often need to be adapted or reinvented. To achieve this, you will have the freedom to explore and develop your own ideas while working collaboratively with a team of quants, developers, and analysts, to combine technical expertise with football knowledge.
You will be based at our London office, at 1 Craven Hill, London, W2 3EN, with the option to work from home one day a week. While we are open to flexible working hours to help you avoid rush hour, we value in-person collaboration and learning opportunities, so we are not considering fully remote candidates at this time.
Requirements
We are looking for smart, ambitious people who enjoy solving challenging problems, and are able to make pragmatic decisions in a dynamic environment. More specifically, you should have:
3+ years of experience applying predictive modelling, machine learning, and probability theory, preferably in sports or gaming/betting industries.
Familiarity with techniques such as Monte Carlo simulation, Bayesian modelling, mixed effects models, Kalman filters, GLMs, and time series forecasting. While expertise in every area isn't expected, you should have a broad awareness of available techniques and tools, and understand the trade-offs of different approaches
Strong Programming skills, ideally in Python
Knowledge of SQL and relational databases
Experience in exploring new datasets, identifying data quality issues, and handling imperfect data effectively
An excellent candidate will also:
Understand and apply expected value and utility principles, both in evaluating betting scenarios and in prioritising projects or analyses
Have a practical approach to problem-solving, balancing attention to detail with the ability to deliver MVPs quickly
Be able to deliver projects independently, making informed and justifiable decisions, while also contributing effectively as part of a team
Be able to communicate complex models and analyses clearly to both technical and non-technical audiences
Have an interest in football and sports analytics
What We Offer
Half yearly bonus opportunities based on company performance
33 days holiday (Including bank holidays)
Competitive contribution matched pensions
Health and well-being benefits:
Private Medical Insurance (including excess coverage)
Health Cash Plan via Bupa
Subsidised gym membership
Daily subsidised office meals
Learning and development budgets to invest in your personal growth
Company and team led engagement activities throughout the year
Fortnightly five-a-side game amongst colleagues
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