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Lead Data Scientist- Sports Betting ML

Lead Data Scientist- Sports Betting ML

Remote

United kingdom

Senior

Full Time

10-02-2026

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Skills

Communication Leadership Python SQL Dynamics Monitoring Research Machine Learning PyTorch TensorFlow Deep Learning Analytics Data Science Mathematics

Job Specifications

About the Role

We're looking for a Lead Data Scientist to head our machine learning model development operation. You'll design, build, and deploy predictive models that estimate sports outcome probabilities, models that directly drive our betting strategy on prediction markets.

This is a hands-on leadership role. You'll own the full model lifecycle from research through production, lead a team of data scientists, and continuously improve our predictive edge.

The role will be fully remote with a generous compensation package.

Responsibilities
Lead the design, development, and deployment of machine learning models for sports outcome prediction
Manage and mentor a team of data scientists and data engineers
Build and validate deep learning architectures (CNNs, Transformers, neural networks) for structured sports data
Develop back testing frameworks and rigorously validate model performance against historical data
Collaborate with trading and engineering teams to integrate models into live betting operations
Ensure data quality, pipeline integrity, and model monitoring in production
Stay current with advances in sports analytics, ML research, and betting market dynamics
Requirements
5+ years of experience as a Data Scientist or ML Engineer, with at least 2 years in a leadership role
Proven experience building sports betting or prediction models- this is essential
Strong expertise in deep learning frameworks (PyTorch, TensorFlow) and techniques (neural networks, CNNs, Transformers)
Advanced proficiency in Python and SQL
Solid foundation in statistics, probability theory, and predictive modelling
Experience deploying ML models to production environments
Excellent communication skills- ability to translate complex findings for non-technical stakeholders
Degree in Computer Science, Data Science, Statistics, Mathematics, Physics, or related quantitative field

About the Company

SIRE leverages prediction markets to generate uncorrelated yield from sports outcomes. Sports markets operate independently of macroeconomic conditions, providing return opportunities when traditional assets are correlated to the downside. Using proprietary data and quantitative models, we identify mispriced probabilities and execute on-chain with institutional-grade risk management. For allocators seeking portfolio diversification beyond traditional assets. Know more