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Baseball Data Science Jobs in Massachusetts (NOW HIRING)

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Baseball Data Science information

What is baseball data science?

Baseball data science is the application of statistical analysis, machine learning, and data management techniques to baseball data to gain insights, improve player performance, and inform team strategies. Data scientists in baseball analyze large datasets such as player statistics, pitch tracking, and game outcomes to uncover patterns and make predictions. Their work supports coaching decisions, scouting, player health monitoring, and front office operations. Baseball data science has become increasingly important with the rise of advanced metrics and technologies like Statcast.

How do baseball data scientists collaborate with coaches and players to translate analytics into on-field improvements?

Baseball data scientists often work closely with coaches and players by presenting data-driven insights in accessible ways, such as visualizations or concise reports. They help translate complex analytics into actionable strategies, like adjusting swing mechanics or defensive positioning. Regular meetings and open communication are key, as data scientists must ensure their recommendations align with team goals and player capabilities. This collaborative approach not only bridges the gap between data and performance but also fosters a culture of continuous improvement.

What are the key skills and qualifications needed to thrive as a baseball data scientist, and why are they important?

To thrive as a Baseball Data Scientist, you need a strong background in statistics, data analysis, and computer science, often supported by a degree in a quantitative field. Familiarity with programming languages like Python or R, experience with SQL databases, and proficiency in data visualization tools are typically required. Strong communication, problem-solving abilities, and a passion for baseball analytics make candidates stand out. These skills are crucial for extracting actionable insights from complex data, supporting decision-making, and driving competitive advantage in baseball operations.

What is the difference between Baseball Data Science vs Baseball Analytics?

AspectBaseball Data ScienceBaseball Analytics
Required CredentialsDegree in Data Science, Statistics, or related fieldDegree in Sports Management, Analytics, or related field
Work EnvironmentData-driven teams, sports organizations, research labsTeam analysis departments, sports teams, consulting firms
Employer & Industry UsageMajor league teams, sports analytics companies, research institutionsMajor league teams, sports media, consulting firms

Baseball Data Science focuses on advanced statistical modeling, machine learning, and data engineering to uncover insights from complex datasets. Baseball Analytics often emphasizes performance metrics, game strategy, and player evaluation using statistical tools. While both roles overlap, Data Science tends to involve more technical data manipulation, whereas Analytics centers on applying insights to game strategies and player decisions.

What are popular job titles related to Baseball Data Science jobs in Massachusetts?

For Baseball Data Science jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Baseball Data Science jobs in Massachusetts look for?

The top searched job categories for Baseball Data Science jobs in Massachusetts are:

Baseball Data Science jobs near you
Infographic showing various Baseball Data Science job openings in Massachusetts as of August 2026, with employment types broken down into 11% Internship, 48% Full Time, and 41% Part Time. Highlights an 100% In-person job distribution.

Data Scientist, Baseball Analytics

Boston Red Sox

Boston, MA • On-site

$75K - $100K/yr

Full-time

Re-posted 24 days ago

Job description

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. 
In addition to the above requirements, all roles within Baseball Operations are expected to effectively demonstrate our universal competencies related to problem solving, teamwork, clarity of communication, and time management, along with embodying our culture of honesty, humility, relentlessness, and commitment to DEIB.
At the Boston Red Sox we go beyond embracing diversity. We’re committed to living by our values, strengthening our community, and creating a workplace where people genuinely feel like they belong. 
 
Too often, job seekers don’t apply to positions because they don’t meet every qualification. If you love this role and are great at what you do, we encourage you to apply. Your unique skills and experiences might just be what we’ve been looking for.
 
Prospective employees will receive consideration without discrimination based on race, religious creed, color, sex, age, national origin, handicap, disability, military/veteran status, ancestry, sexual orientation, gender identity/expression or protected genetic information.