Mid/Senior Quant

BettingJobs
Greater London
1 week ago
Applications closed

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BettingJobsis partnering with a renowned sports analytics company that serves clients in the iGaming industry in their search for a talented Quantitative Analyst to join their London based team.


The successful candidate will use the extensive datasets 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.


Key Requirements:


  • 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

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