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Description
The Los Angeles Dodgers currently have a job opportunity for a Quantitative Analyst. Following you will find a brief description of the job and application process. For additional information, please contact [email protected].
Title: Quantitative Analyst
Department: Baseball Research & Development
Status: Full-Time
Pay Rate: $90,000 - $110,000*
Reports to: Director, Quantitative Analysis
- Compensation rates vary based on job-related factors, including experience, job skills, education, and training.
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
- 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
- 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
- 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
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LOS ANGELES DODGERS LLC is an equal opportunity employer.
LOS ANGELES DODGERS LLC is firmly committed to providing equal opportunity for all qualified applicants from every race, creed, and background. LOS ANGELES DODGERS LLC is also firmly committed to complying with all applicable laws and governmental regulations at the state and local levels which prohibit discrimination.
LOS ANGELES DODGERS LLC considers all applicants without regard to national origin, race, color, religion, age, sex, sexual orientation, disability, military status, citizenship status, pregnancy or related medical conditions, marital status, ancestry-ethnicity, or any other characteristic protected by applicable state or federal civil rights law. The Immigration Reform and Control Act requires that LOS ANGELES DODGERS LLC obtain documentation from every individual who is employed, which verifies their identity and authorizes their right to work in the United States.
LOS ANGELES DODGERS LLC is committed to the full inclusion of all qualified individuals. As part of this commitment, LOS ANGELES DODGERS LLC will ensure that persons with disabilities are provided reasonable accommodations for the hiring process. If reasonable accommodation is needed, please contact [email protected].
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