DEPARTMENT OVERVIEW:
Baseball Analytics is the quantitative research and data science group within Baseball Operations. We develop statistical models, machine learning algorithms, and analytical tools that support decision-making across Baseball Operations including player acquisition, player development, and player optimization. Core responsibilities include predictive modeling, applied research, experimentation, and communicating technical findings to inform baseball decisions.
POSITION OVERVIEW:
The Boston Red Sox seek a Data Scientist for the club’s Baseball Analytics department to develop, evaluate, and optimize predictive models that enhance decision-making across all aspects of Baseball Operations. Operating in a dynamic and intellectually stimulating environment, the Data Scientist will collaborate closely with the Baseball Analytics team and other Baseball Operations stakeholders to influence player personnel decisions and strategic initiatives. This role offers a unique opportunity to apply advanced statistical techniques and data science to shape the team's future direction.
The successful candidate will possess strong analytical skills, a deep understanding of baseball, and the ability to communicate technical concepts to non-technical audiences effectively. The specific role, level, and compensation package will be tailored to the selected candidate's qualifications and experience. Applications are encouraged from individuals with varying levels of expertise in the field.
The salary range for this position is $75,000–$100,000, based on relevant experience and internal equity. Our full-time employees also receive a comprehensive benefits package, including healthcare, retirement plans, paid time off, and more.
RESPONSIBILITIES:
- Design and maintain robust predictive models and data pipelines to generate insights for player evaluation, acquisition, development, and performance optimization.
- Craft compelling written reports and data visualizations to effectively communicate complex analyses to diverse audiences, including both technical specialists and Baseball Operations leadership.
- Partner with the Baseball Systems team to seamlessly integrate new analytical findings into team applications and proactively identify and address data quality issues.
- Continuously monitor and evaluate cutting-edge analytics and research from public and academic spaces to recommend innovative ideas, methodologies, and technologies that can enhance on-field performance.
COMPETENCIES
- Understanding of modern statistical and machine learning methods and an advanced proficiency with popular data science languages and libraries.
- Practical understanding of how to approach research questions to drive actionable insights.
- Able to visualize, present and disseminate analyses to a diverse group of stakeholders (leadership, coaches, players, scouts, etc.) in a clean, intuitive, and engaging way.
ADDITIONAL QUALIFICATIONS:
- PhD or master's degree in a quantitative field (such as statistics, engineering, applied mathematics, physics, quantitative social sciences, computer science, computer vision, or operations research) or equivalent professional experience.
- Proficiency in SQL and programming languages such as R or Python.
- A passion for baseball and a strong desire to contribute to building a championship-winning team.
Boston Red Sox Boston, Massachusetts, USA Office
4 Jersey St, Boston, MA, United States, 02215
Similar Jobs
What you need to know about the Boston Tech Scene
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
