Junior Quantitative Analyst
- Compensation rates vary based on job-related factors, including experience, job skills, education, and training.
- Assist in the development, refinement, and maintenance of models of baseball, integrating new data sources and methods where appropriate
- Collaborate across the organization to identify and answer important research questions
- Write clear, reliable code for data analysis and model implementation
- Learn, implement, and develop best practices for model development
- Participate in internal seminars and code reviews to grow technical and baseball knowledge
- Bachelor’s or Master’s degree in a quantitative field or equivalent experience
- Demonstrated experience applying statistics and machine learning to research problems
- Strong communication skills
- Passion for baseball
- Core Skills: Proficiency in Python, SQL, and version control
- Deep learning track
- Exposure to deep learning frameworks (Jax/PyTorch/TensorFlow)
- Experience working with time-series, image, or video data
- Bayesian modeling track
- Coursework or projects involving Bayesian statistics and probabilistic programming (NumPyro, PyMC, or Stan)
- Familiarity with forecasting, uncertainty quantification, or hierarchical modeling
- Understanding of physics and biomechanics
- Experience with open-source contributions or academic research
- Experience with agentic coding tools
- Experience with data analysis in sports, robotics, health wearables, autonomous systems, or aerospace. Baseball research experience is a plus.
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