Data Scientist, Baseball Analytics

Department Overview

The Baseball Analytics group is the quantitative research and data science function inside Baseball Operations. Its work centers on building statistical models, machine learning methods, and analytical systems that guide decisions related to player acquisition, player development, and player optimization. The team’s work includes predictive modeling, applied research, experimentation, and translating technical results into insights that support baseball decision-making.

Role Overview

The Boston Red Sox are hiring a Data Scientist for the Baseball Analytics department to design, test, and improve predictive models that strengthen decision-making across Baseball Operations. In this fast-paced, intellectually engaging setting, the role will work closely with the Baseball Analytics team and broader Baseball Operations partners to influence roster decisions and strategic priorities.

This is a strong opportunity for someone who wants to apply advanced statistical and data science methods to help shape the team’s long-term direction. The organization is looking for a candidate with solid analytical ability, a deep understanding of baseball, and the skill to explain technical ideas clearly to non-technical audiences.

The exact level of the role and the compensation package will be aligned to the chosen candidate’s background and experience. Candidates with different levels of experience are encouraged to apply.

The annual salary range for this position is $75,000 to $100,000, depending on relevant experience and internal equity. Full-time employees are eligible for a broad benefits package that includes healthcare, retirement plans, paid time off, and additional benefits.

Responsibilities

• Build, improve, and support predictive models and data workflows that produce insights for player evaluation, acquisition, development, and performance optimization.
• Prepare written analyses and visual presentations that make complex findings understandable for both technical teammates and Baseball Operations leadership.
• Work with the Baseball Systems team to incorporate new analytical outputs into team tools and to detect and resolve data quality concerns.
• Track and assess public and academic research in modern analytics, then recommend promising techniques, methods, and technologies that could improve on-field results.

Competencies

• Strong command of current statistical and machine learning approaches, along with advanced use of common data science languages and libraries.
• Ability to frame research questions in a way that leads to practical, decision-ready insights.
• Experience presenting and sharing analysis with a wide range of stakeholders, including leadership, coaches, players, and scouts, in a clear and engaging format.

Additional Qualifications

• A PhD or master’s degree in a quantitative discipline such as statistics, engineering, applied mathematics, physics, quantitative social sciences, computer science, computer vision, or operations research, or equivalent professional experience.
• Working knowledge of SQL and programming languages such as R or Python.
• Strong enthusiasm for baseball and a desire to help build a championship-caliber team.

Additional Information

All roles in Baseball Operations are expected to demonstrate the organization’s universal competencies, including problem solving, teamwork, clear communication, and time management. Team members are also expected to reflect the club’s culture of honesty, humility, relentlessness, and commitment to DEIB.

The organization emphasizes belonging, community, and values-based workplace culture. It also encourages candidates to apply even if they do not meet every listed qualification, as strong skills and relevant experience may still make them a good fit.

Employment decisions are made without discrimination based on race, religious creed, color, sex, age, national origin, handicap, disability, military or veteran status, ancestry, sexual orientation, gender identity or expression, or protected genetic information.