Data Scientist - Research and Development

Position Overview

The Pittsburgh Pirates are a storied franchise in Major League Baseball, reinventing themselves on every level. They boldly and relentlessly pursue excellence by purposefully developing a player and people-centered culture, deeply connecting with fans, partners, and colleagues, passionately creating lifetime memories for families and friends, and meaningfully impacting their communities and the game of baseball.

As a Data Scientist on the Pirates Research & Development team, you will transform a wealth of baseball data—from box scores and player tracking to video and biomechanics—into actionable insights. You will work closely with data scientists, analysts, and software engineers across Baseball R&D and other stakeholders in Baseball Operations to turn statistical and machine learning models into decision tools.

Equal Opportunity Employer: The Pittsburgh Pirates are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.

Key Responsibilities

• Design, build, validate, and deploy statistical and/or machine-learning models to support facets of baseball operations, including scouting, player acquisition, player development, and on-field decision making.
• Build tools, prototypes, and visualizations to translate complex data and model results into actionable insights for coaches, players, and decision-makers.
• Communicate results and insights clearly to both technical and non-technical audiences.
• Partner with data engineers in building scalable data pipelines and maintaining data quality.
• Stay abreast of new data sources, analytical techniques, and research.
• Help the organization experiment, learn, and iterate.

Required Qualifications

• Degree (or equivalent experience) in a quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Economics, Machine Learning, Biomechanics, Engineering, Operations Research).
• Demonstrated experience applying complex statistical and/or machine learning tools to real-world problems.
• Proficiency in a programming language such as Python or R for data analysis and modeling.
• Ability to communicate complex quantitative concepts clearly, both in writing and verbally.
• Proven experience collaborating on data science projects.
• Authorized to work lawfully in the United States.

Preferred Qualifications

• Familiarity with advanced statistical techniques (e.g., fixed-effect/ random-effect models, generalized additive models, Bayesian modeling, probabilistic programming).
• Experience with machine-learning/deep-learning frameworks (e.g., PyTorch, Tensorflow), especially applied to high-dimensional, spatiotemporal, or biomechanical data.
• Background in computer vision, biomechanics, sports science, or modeling dynamic physical systems.
• Prior experience in a sports analytics context; baseball is a plus.
• Experience with database languages (e.g., SQL) and working with large or relational datasets.