Quantitative Researcher

Overview

In this role, you will develop statistical models to estimate probabilities of sports outcomes for a sports betting hedge fund. You join a highly skilled team focused on building and refining probabilistic models and extracting insights from diverse data sources. You will explore, test, and optimise modelling approaches to support decision-making and performance. This is a chance to work at the intersection of quantitative research and sports analytics, shaping scalable modelling approaches.

Responsibilities

• Develop probabilistic and statistical models to predict sports outcomes
• build and refine models, ensuring quality and evolution over time
• explore multiple modelling approaches and test their performance
• extract meaningful information from diverse sporting and market data sources
• work with a team of quants to tackle complex sporting questions
• apply GLMs, BMMs, Kalman filters, MCMC and TrueSkill in modelling
• contribute to the research and development of sports modelling capabilities

Key requirements

• 1+ years of experience
• Statistics graduate/post-graduate
• Electronic Trading Experience
• Python, TensorFlow
• Straight As at A level (or equivalent)
• Kaggle profile (or other practical statistical experience)
• Python stack (numpy, pandas, etc.)
• R
• TensorFlow

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