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Baseball Data Analytics Jobs (NOW HIRING)

Windquest

Sr Data Analyst - Crecera Brands

Minneapolis, MN · On-site

$75K - $110K/yr

Sr. Data Analyst ABOUT THE COMPANY Crecera Brands is the driving force behind Sportsman's Guide, Salt Strong, The Golfer's World, Play Baseball and Play Softball, five of America's leading retailers ...

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How much do baseball data analytics jobs pay per year?

As of Jun 27, 2026, the average yearly pay for baseball data analytics in the United States is $81,518.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $96,500.00 per year, depending on experience, location, and employer.

How to become a data analyst for a sports team?

To become a data analyst for a sports team, you typically need a bachelor's degree in statistics, data science, or a related field, along with strong skills in data analysis tools like Excel, SQL, and programming languages such as Python or R. Experience with sports data, knowledge of baseball metrics, and familiarity with data visualization software can enhance your prospects. Internships or entry-level roles in sports analytics can provide practical experience and industry connections.

What are the key skills and qualifications needed to thrive in the Baseball Data Analytics position, and why are they important?

To thrive in Baseball Data Analytics, you need strong statistical analysis capabilities, proficiency in sports analytics, and a background in mathematics, computer science, or a related field. Familiarity with data visualization tools, SQL databases, Python or R programming, and platforms like TrackMan or Statcast is typically required. Excellent communication, teamwork, and critical thinking are valuable soft skills to clearly present insights and collaborate with coaching staff. These abilities are essential for transforming complex data into actionable strategies that improve team performance and decision-making.

What is a Baseball Data Analytics job?

A Baseball Data Analytics job involves collecting, analyzing, and interpreting baseball data to provide insights that help teams make better decisions. Analysts work with player performance metrics, in-game statistics, and predictive models to assess talent, optimize strategies, and improve overall team performance. These roles require strong statistical and programming skills, often using tools like SQL, Python, and R. Many analysts work for MLB teams, minor league affiliates, or sports technology companies.

What are some typical daily tasks for someone working in Baseball Data Analytics?

A professional in Baseball Data Analytics often spends their day collecting and cleaning player and game data, performing in-depth statistical analyses, and developing models to evaluate player performance or inform tactical decisions. They regularly collaborate with coaches, scouts, and front-office staff to translate complex findings into actionable advice. In addition, they may create visualizations or reports using tools like Tableau or Power BI and stay updated with new analytical methods and technologies in sports. This dynamic environment offers opportunities to contribute directly to the team’s competitive strategy while constantly learning new industry trends.

How to be a baseball data analyst?

To become a baseball data analyst, develop strong skills in statistics, data analysis, and programming languages such as Python or R. Gain experience with sports data, learn to use analytics tools like SQL and Excel, and understand baseball metrics and game strategies. A background in sports management or a related field, along with internships or projects, can also enhance your prospects.

Does analytics work in baseball?

Baseball data analytics is widely used to evaluate player performance, inform strategic decisions, and improve team outcomes. Analysts often work with tools like SQL, R, or Python to interpret large datasets, making analytics a valuable part of modern baseball operations.

How much do baseball data analysts make?

Baseball data analysts typically earn between $50,000 and $100,000 annually, depending on experience, education, and the level of the organization. Entry-level positions may start lower, while experienced analysts working with major league teams or advanced analytics roles can earn higher salaries, often supplemented by bonuses or benefits. Proficiency in statistical tools and data visualization software is often required for higher-paying roles.
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Baseball Data Analytics jobs near you
Infographic showing various Baseball Data Analytics job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 3% Full Time, 92% Part Time, 2% Contract, and 2% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $81,518 per year, or $39.2 per hour.
Sports Data Analyst

Sports Data Analyst

Swish Analytics

San Francisco, CA

Full-time

Posted 12 hours ago

Job description

Company Description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.

Duties:

  • Work closely with Data Scientists and Engineers to diagnose and treat data pipeline integrity issues

  • Detect data inaccuracies such as missing, out of range or otherwise incorrect on-field data

  • Source origins of data inaccuracies through data pipeline dependencies and python code base

  • Define data validation tests to flag future game errors

  • Research accurate roster active statuses, primary positions and game participation

  • Validate data changes after logic updates

  • Production model feature deep dives to explain project market lines

  • Clearly document findings

  • Develop intimate familiarity with existing databases and construct metadata references

  • With guidance, support lead Data Scientists in feature development and model analysis

Requirements:

  • Bachelor's Degree in Computer Science, Data Science or similar major

  • Minimum of 1 year of experience in football data analysis

  • Deep knowledge of football, basketball or baseball; including roster compositions of professional and college teams, general gameplay strategies, and typical in-game scenarios

  • Data Extraction, Wrangling and Analysis in Python

  • Strong SQL querying skills

  • Attention to detail

Preferred:

  • Strong Python data management programming skills

  • Data Visualization experience with a user application like Streamlit

  • Deep knowledge of a second sport including football, basketball, baseball, hockey or tennis

  • Exposure to the data science process and tech stack

  • Anomaly Detection Techniques

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.