Senior Sports Quantitative Modeller

Hybrid; City Of London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading sports analytics firm in London seeks a Senior Sports Quantitative Modeller. You will develop and implement quantitative models, focusing on BetBuilder products, while mentoring junior team members. The ideal candidate has proven experience in quantitative analysis and strong proficiency in Python, along with a solid understanding of statistical modeling techniques. The position offers opportunities to drive innovation and significantly impact the business.

Qualifications

• Proven experience as a Quantitative Analyst/Modeller.
• Deep expertise in mathematical and statistical modeling.
• Highly proficient in Python.
• Strong experience in backtesting and validation of models.
• Excellent communication and collaboration skills.

Responsibilities

• Design, develop, and implement advanced mathematical models.
• Backtest and validate models to ensure accuracy and profitability.
• Drive quantitative modeling initiatives for BetBuilder products.
• Provide technical guidance and mentorship to junior team members.
• Present findings persuasively to stakeholders.

Skills

Quantitative analysis

Statistical modeling

Python

Backtesting

Data visualization

Problem-solving

Tools

Tableau

matplotlib

Docker

Kubernetes

Job description

The Senior Sports Quantitative Modeller is a senior individual contributor and an expert in mathematical and statistical modelling. 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 team members.

Responsibilities

Design, develop, and implement advanced mathematical and statistical models, 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 other teams to ensure models are well-understood, seamlessly integrated, and align with best practices and system architecture.

Provide technical guidance and mentorship to more junior team members on modeling techniques, best practices, and project execution.

Proactively identify opportunities for advanced quantitative modeling to address business challenges and drive innovation.

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.

Requirements

• Proven experience as a Quantitative Analyst/Modeller with a track record of successfully leading and delivering impactful quantitative models.
• Deep expertise in mathematical and statistical modeling 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 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.
• 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).

The above list of duties is not exclusive or exhaustive and the post holder will be required to undertake tasks that are reasonably expected within the scope and grading of the post.