Description

A leading sports betting fund is seeking a Junior Quantitative Researcher to join its expanding quantitative research team. This is an exciting opportunity for an analytically minded individual with a passion for sports modelling, data science, and statistics to contribute to cutting-edge research and model development within a high-performing environment.

Key Responsibilities

• • Assist senior quantitative researchers in delivering research and model development projects.
  • Support clients and internal teams by:
  • Developing, maintaining, and improving the mathematical libraries that power predictive models and analytical tools.
  • Building and maintaining software systems that deliver model outputs into production.
  • Perform statistical analysis of datasets, test hypotheses, and communicate findings effectively to key stakeholders.
  • Contribute to the ongoing enhancement of core programming libraries.
  • Participate in at least one professional development event annually-such as a conference, workshop, or networking event-focused on areas like sports analytics, statistics, machine learning, or gambling.

Skills & Experience

Required

• • MSc in Statistics , Data Science , Mathematics , or another quantitative discipline (e.g., Computer Science, Engineering, Finance) with a strong statistical component.
  • Prior experience in a role involving significant statistical analysis, demonstrating skills beyond academic study.
  • Programming experience and a willingness to learn and work in R .
  • Demonstrated passion for sports modelling-through personal projects, academic research, or independent analyses.
  • Commitment to continuous learning and professional growth.
  • Curiosity and enthusiasm for exploring new technologies and programming languages.
  • Eligibility to work in the UK .

Preferred

• • Strong interest in horse racing , supported by prior modelling or data analysis projects.
  • Understanding of sports betting markets .
  • Familiarity with statistical and machine learning methods (e.g., GBM, Torch, CNN, LSTM, NLP, GNN).
  • Experience with additional programming languages (e.g., Python, C++, Julia).
  • Working knowledge of database systems (e.g., SQL, MongoDB, Redis, Postgres).
  • Experience with version control , code reviews , and merge requests .
  • Familiarity with CI/CD pipelines and test-driven development (TDD) .