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Baseball Data Science Jobs (NOW HIRING)

Ex Parte, Inc

Lead Data Engineer

Bethesda, MD · On-site +1

$122K - $146K/yr

Think of it like Moneyball, but for a market more than 20x the size of Major League Baseball. You ... Computer Science, Engineering, Mathematics or related field Additional Information All your ...

Ex Parte, Inc

Lead Data Engineer

Bethesda, MD · On-site

$122K - $146K/yr

Think of it like Moneyball, but for a market more than 20x the size of Major League Baseball. You ... Computer Science, Engineering, Mathematics or related field Additional Information All your ...

The New York Mets

Applied AI Engineer

Queens, NY · On-site

$180K - $200K/yr

This role sits at the intersection of Baseball Systems (software engineering), Data Engineering ... Bachelor's degree in Computer Science or equivalent practical experience. * 5+ years of ...

AEG

Hitting Coach - Scottsdale, AZ

Scottsdale, AZ · On-site

$17.50 - $23.25/hr

Hourly, Rate Dependent on Location Driveline Baseball, a data-driven player development ... Collaborate with our sports science team to optimize training outcomes and advance research ...

AEG

Hitting Coach - Kent, WA

Kent, WA · On-site

Hourly, Rate Dependent on Location Driveline Baseball, a data-driven player development ... Collaborate with our sports science team to optimize training outcomes and advance research ...

AEG

Hitting Coach - Tampa, FL

Tampa, FL · On-site

Hourly, Rate Dependent on Location Driveline Baseball, a data-driven player development ... Collaborate with our sports science team to optimize training outcomes and advance research ...

Rangers Baseball LLC

Network Engineer

Arlington, TX · On-site

Bachelor's degree in the field of Computer Science, Data Science, Computer Information Systems, or related field, and/or 5+ years equivalent work experience. * 3-5 years of experience supporting ...

AEG

Assistant Groundskeeper

Baltimore, MD · On-site

$70K - $80K/yr

Prepare the playing surface to Major League Baseball standards for all home games, practices ... Bachelor's degree in Turfgrass Science, Agronomy, Plant Science, Horticulture, Sports Turf ...

AEG

Pitching Trainer

Scottsdale, AZ · On-site

Hourly, location dependent Driveline Baseball, a data-driven player development organization, is ... Progress towards a degree in exercise science, biomechanics, or related field * Published work in ...

Ex Parte, Inc

Senior Data Engineer

Bethesda, MD · On-site

$113K - $153K/yr

Think of it like Moneyball, but for a market more than 20x the size of Major League Baseball. You ... Computer Science, Engineering, Mathematics or related field Additional Information All your ...

Ex Parte, Inc

Senior Data Engineer

Bethesda, MD · On-site +1

$113K - $153K/yr

Think of it like Moneyball, but for a market more than 20x the size of Major League Baseball. You ... Computer Science, Engineering, Mathematics or related field Additional Information All your ...

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Baseball Data Science information

See salary details

$41.5K

$142.5K

$201K

How much do baseball data science jobs pay per year?

As of Sep 15, 2026, the average yearly pay for baseball data science in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

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.

More about Baseball Data Science jobs

What cities are hiring for Baseball Data Science jobs?

Cities with the most Baseball Data Science job openings:

What are the most commonly searched types of Baseball Data Science jobs?

The most popular types of Baseball Data Science jobs are:

What states have the most Baseball Data Science jobs?

States with the most job openings for Baseball Data Science jobs include:

What are popular job titles for Baseball Data Science?

Popular job titles for Baseball Data Science:

Infographic showing various Baseball Data Science job openings in the United States as of September 2026, with employment types broken down into 5% Internship, 69% Full Time, 24% Part Time, and 2% Contract. Highlights an 93% In-person, 2% Hybrid, and 5% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.

Lead Data Engineer

Bethesda, MD • On-site, Remote

Ex Parte, Inc
Software Development • 1 - 10 employees
Learn more about Ex Parte, Incexternal

$122K - $146K/yr

Full-time

Re-posted 7 days ago

Job description

Company Description
Ex Parte provides our customers with the data and insight to make smart and informed decisions on the most important legal issues facing their organizations.
We are is looking for talented, enthusiastic senior data engineers who share our passion for big data, AI, and machine learning and are excited by seemingly-impossible challenges. As an early employee, you must be amazingly entrepreneurial and thrive in a fast-paced environment where the solutions aren't predefined.
Every year, corporations spend more than $250B on litigation in the United States alone. And yet, critical decisions such as whether to litigate or settle, or where to file suit or which attorney to hire, are all made the same way they were 100 years ago.
We are applying artificial intelligence, machine learning, and natural language processing to provide our customers with the insight they need to make highly informed decisions and gain a winning advantage. Think of it like Moneyball, but for a market more than 20x the size of Major League Baseball.
Job Description
You'll lead a team that owns the AI self-service portal and the related set of microservices. You'll work with a cross-functional team of engineers to contribute to our data platform. The role also offers the opportunity to grow into either more back-end or ML/AI work depending on your interests and experience.
In this role, you can expect to:
• Work directly with product owners and data experts to build products that solve to solve complex client problems
• Build and support a distributed platform supporting all ExParte data
• Work across our product, primarily on the data pipelines
• Interface directly with internal teams
• Evaluate software and implementation options and document them for technical teams
• Work with data analysts to collect insight on possible data collection efficiencies and identify automation potential for manual workflows
• Integrate best qualitative practices in program design and development.
• Be a part of a distributed team (we're in North America and Europe)
• Work with Azure cloud and Databricks
• Develop technical architectures and specific implementations to meet business needs.
• Guide the team's software engineering best practices by documenting standards and completing code reviews.
• Troubleshoot new and existing code and provide feedback and solutions to structural issues in the codebase as they arise.
• Advise on the feasibility of nonfunctional requirements and ensure the successful implementation of features while meeting those requirements.
Qualifications
Requirements:
• 3+ years experience with RDBMS and T-SQL.
• 3+ years experience with NoSQL and DataLakes.
• 3+ Knowledge of Spark, Python, or Scala
• Strong familiarity with map/reduce programming models
• Proficiency in writing production-quality code
• Deep expertise in database schema design, optimization, and scalability
• Experience with Azure or AWS cloud-based service-oriented architecture
• Solid understanding of testing pyramid (unit, integration, black box, service)
• Experience working in an Agile/Scrum environment
• Strong analytical and problem-solving skills
• Good time management and organizational skills
• Ability to work on challenging issues independently or in a team environment
• Ability to learn and adapt quickly to new technologies and environments
• Strong communication skills
Nice-to-have's:
• Experience with Databricks or Azure ML
• Experience applying machine learning algorithms to solve complex data mining problems
• Experience with BI tools
• Understanding of cloud platforms and providers and DevOps
• Bachelor's Degree in Computer Science, Engineering, Mathematics or related field
Additional Information
All your information will be kept confidential according to EEO guidelines.

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