The Los Angeles Dodgers are a professional baseball team based in Los Angeles, California. The Dodgers are members of the National League West division of Major League Baseball (MLB). The team originated in Brooklyn, New York, where it was known by a number of nicknames before becoming the Dodgers definitively by 1932. The team moved to Los Angeles before the 1958 season. They played their first four seasons in Los Angeles at the Los Angeles Memorial Coliseum before moving to their current home of Dodger Stadium, the third-oldest ballpark in Major League Baseball (trailing Fenway Park and Wrigley Field).

Since 2012, the Los Angeles Dodgers have been led by Guggenheim Baseball Management and a successful team of owners consisting of Mark Walter, Magic Johnson, Todd Boehly, Bobby Patton, Jr., Peter Guber, Billie Jean King and Ilana Kloss. Under this ownership group, the Dodgers have continued to set attendance records and achieved the team's first World Series championship in over 30 years. Andrew Friedman is the Dodgers’ President, Baseball Operations and the Manager is Dave Roberts, who recently agreed to a four-year contract to manage club through 2022. The Dodgers front office comprises approximately 300 full-time and 1,400 part-time employees.

The Dodgers have won seven World Series titles and 21 National League pennants. Eight Cy Young Award winners have pitched for the Dodgers, winning a total of ten Cy Young Awards (both MLB records). The team has also produced 12 Rookie of the Year award winners, including four back-to-back from 1979–1982 and five back-to-back from 1992–1996, the longest consecutive streaks in Major League Baseball.

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

Mentor junior analysts and represent the Dodgers at conferences, workshops, and campus events

Basic Requirements/Qualifications:

Experience: 2+ years of experience building and evaluating predictive models in industry or equivalent academic experience

Core Skills: Proficiency in Python, SQL, version control, and reproducible research practices

Preferred Expertise:

Deep learning track

You have built and evaluated deep-learning models for tasks such as detection, segmentation, motion forecasting, or anomaly detection in jax, PyTorch, or a similar tensor library

You have built models using data from spatial sensors

You have built models that incorporate physics, domain constraints, or graph structure

Bayesian modeling track

You have built and evaluated Bayesian hierarchical models

You have implemented Gaussian-process, state-space, or other latent-factor structures for time-series forecasting in domains with sparse or noisy data.

You have written probabilistic models in NumPyro, PyMC, or Stan with custom likelihoods and priors

You have applied predictive distributions to decision-making in some domain

Additional signals of impact:

Understanding of physics and biomechanics

Experience with agentic coding tools

Experience deploying ML systems using terabytes of data

Success applying data analysis in sports, robotics, health wearables, autonomous systems, or aerospace. Baseball research experience is a plus.

Experience writing queries on large SQL databases, engineering ETL pipelines, and/or working with data lakehouses