Data Scientist - Sports Betting

Role Overview

We are seeking a Data Scientist to join our Sports Betting division, focused on developing predictive analytics tools for pre-match and in-play sports betting products.

Key Responsibilities

• Design, develop, and assess predictive models using machine learning and statistical techniques, emphasizing probabilistic and Bayesian methodologies.
• Manage the full modeling pipeline including feature engineering, model training, validation, and deployment.
• Utilize Python and SQL to query, cleanse, and analyze datasets to identify key trends and support model creation.
• Incorporate AI-assisted tools to enhance and expedite daily workflows.
• Maintain high standards in model development through version control, thorough testing, and comprehensive documentation.

Candidate Profile

• Passionate about sports, understanding the data context and market dynamics relevant to sports betting.
• Strong foundation in machine learning, both supervised and unsupervised algorithms, classical statistics, and expertise in probabilistic models, uncertainty quantification, and Bayesian inference.
• Experience with end-to-end model development lifecycle, including data processing, feature and model selection, and evaluation.
• Proven hands-on experience building and validating quantitative models in data science contexts.
• Proficient in Python and SQL for data manipulation, feature engineering, and modeling tasks.
• Effective communicator able to present insights clearly to technical and non-technical stakeholders.

Additional Assets

• Familiarity with Monte Carlo simulations or probabilistic simulation methods.
• Experience using AI-enhanced coding platforms such as Claude Code or Cursor and willingness to integrate AI tools into modeling workflows.

Desired Attributes

• Inquisitive mindset focused on understanding underlying causes and customer behavior through data.
• Collaborative work approach, contributing to shared knowledge, codebases, and engaging constructively with peers.
• Commitment to continuous learning and applying emerging data science advances.

Benefits

• Hybrid work model based at our London (Farringdon) office with in-office presence approximately two days per week.
• Competitive salary aligned with external benchmarking and eligibility for bonus programs.
• Comprehensive private health insurance, occupational life cover, and income protection plans.
• Personal days including birthday and wellness days.
• Supportive AI-forward culture, including access to Claude Code Premium subscription.