Lead Data Scientist- Sports Betting ML
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, previous experience with building sports betting models is essential.
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