The Los Angeles Dodgers are looking for quantitative baseball researchers to turn data into actionable insights through the use of mathematical and statistical models. Analysts build and evaluate models, engineer and orchestrate model deployment, and provide data-driven insights to coaches and front office decision-makers on decisions regarding on-field strategy, player development, and player evaluation.

We are especially interested in candidates with either (1) demonstrated strength in deep learning with applications to spatiotemporal data or (2) demonstrated strength in Bayesian hierarchical modeling & probabilistic forecasting. 

Essential Duties/Responsibilities:

• Develop, refine, and maintain models of baseball, integrating new data sources and methods where appropriate
• Collaborate across the organization to identify important research questions and translate model outputs into actionable recommendations for player evaluation, development, and in-game strategy
• Own production code end-to-end: data management, version control, CI/CD, testing, deployment, and monitoring
• Develop internal tools and facilitate code reuse