Senior Sports Quantitative Modeller

A Senior Sports Quantitative Modeller is a senior individual contributor and an expert in mathematical and statistical modeling, specifically for sports betting. This role is responsible for deriving new markets, understanding complex statistical distributions, and building robust, accurate quantitative models, particularly for BetBuilder products. They operate autonomously, owning the full lifecycle of their projects from conception to deployment, and providing technical guidance to junior modellers.

This role reports directly to the Data Science Manager and is an integral part of our Data Science - Core Modeling function.

Key Responsibilities

• Design, develop, and implement advanced mathematical and statistical models for sports betting, with a primary focus on deriving new markets and enhancing existing offerings.
• Possess a deep understanding of complex statistical distributions and leverage techniques such as Monte Carlo simulations in model development.
• Rigorously backtest and validate models to ensure their robustness, accuracy, and profitability in real-world betting scenarios.
• Drive and lead quantitative modeling initiatives, with a particular focus on BetBuilder products, from initial concept through to production deployment.
• Operate with a high level of autonomy, owning and driving projects and solutions from conception to deployment, including managing own workload and project milestones.
• Collaborate closely with Sports Trading, Product, and Engineering teams to ensure models are well-understood, seamlessly integrated, and align with engineering best practices and system architecture.
• Provide technical guidance and mentorship to more junior quantitative modellers on modeling techniques, best practices, and project execution.
• Proactively identify opportunities for advanced quantitative modeling to address business challenges and drive innovation within the sports betting domain.
• Present complex quantitative findings and project outcomes clearly and persuasively to both technical and non-technical stakeholders, including senior leadership.
• Create basic reports and visualisations using tools such as Tableau to communicate model performance and insights.

Job requirements Required Skills and Experience

• Proven experience as a Quantitative Analyst/Modeller with a track record of successfully leading and delivering impactful quantitative models in a production environment.
• Deep expertise in mathematical and statistical modeling, specifically applied to sports betting, including a strong understanding of complex statistical distributions and Monte Carlo simulations.
• Highly proficient in Python for all modeling, analysis, and data manipulation work.
• Strong experience in backtesting, validation, and performance evaluation of quantitative models.
• Solid understanding of the end-to-end model development and deployment lifecycle in a production environment.
• Excellent communication, interpersonal, and collaboration skills, with proven ability to work effectively with cross-functional teams (Trading, Product, Engineering) and manage stakeholder expectations.
• Experience in deriving markets for various sports; experience with US sports is a valuable addition.
• High attention to detail, precision in delivery, and strong problem-solving abilities.
• Demonstrated ability to manage own workload and lead projects with a high degree of self-direction.
• Experience with data visualisation libraries (e.g., matplotlib, seaborn, plotly) and creating basic reports in BI tools like Tableau.

Desirable Skills (Nice to Have)

• General Machine Learning expertise.
• Familiarity with big data concepts or platforms (e.g., PySpark, Hive) for data extraction and manipulation.
• Experience with version control systems (e.g., Git) and MLOps principles.
• Exposure to containerisation concepts (e.g., Docker) or job scheduling tools (e.g., Kubernetes).

Growth Path

This role represents a senior individual contributor path focused on deep quantitative expertise in sports modeling, with potential for even broader technical influence or specialisation within the quantitative domain.