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Baseball Data Science Jobs in Pennsylvania (NOW HIRING)

UPMC

Physician Neurology - Competitive Salary

Altoona, PA · On-site

$315K - $393K/yr

Research funding for clinical, basic, data science, and translational studies in the UPMC Neurology ... Altoona is home to a professional baseball team, the Altoona Curve, which is a Pittsburgh Pirates ...

UPMC

Neurology job in Altoona PA

Altoona, PA · On-site

$315K - $393K/yr

Research funding for clinical, basic, data science, and translational studies in the UPMC Neurology ... Altoona is home to a professional baseball team, the Altoona Curve, which is a Pittsburgh Pirates ...

UPMC

Neurology job in Altoona PA

Altoona, PA · On-site

$315K - $393K/yr

Research funding for clinical, basic, data science, and translational studies in the UPMC Neurology ... Altoona is home to a professional baseball team, the Altoona Curve, which is a Pittsburgh Pirates ...

UPMC

Physician Neurology - Competitive Salary

Altoona, PA · On-site

$315K - $393K/yr

Research funding for clinical, basic, data science, and translational studies in the UPMC Neurology ... Altoona is home to a professional baseball team, the Altoona Curve, which is a Pittsburgh Pirates ...

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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 the most commonly searched types of Baseball Data Science jobs in Pennsylvania?

The most popular types of Baseball Data Science jobs in Pennsylvania are:

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

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

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

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

What cities in Pennsylvania are hiring for Baseball Data Science jobs?

Cities in Pennsylvania with the most Baseball Data Science job openings:

Baseball Data Science jobs near you
Infographic showing various Baseball Data Science job openings in Pennsylvania as of August 2026, with employment types broken down into 11% Internship, 55% Full Time, and 34% Part Time. Highlights an 100% In-person job distribution.

Data Scientist - Research and Development

Pittsburgh Associates

Pittsburgh, PA • On-site

Full-time

Re-posted 11 days ago

Key responsibilities

  • Design, build, validate, and deploy statistical and/or machine-learning models to support baseball operations.

  • Build tools, prototypes, and visualizations to translate complex data and model results into insights for coaches, players, and decision-makers.

  • Partner with data engineers to build scalable data pipelines and maintain data quality.

Job description

The Pirates Why

The Pittsburgh Pirates are a storied franchise in Major League Baseball who are reinventing themselves on every level. Boldly and relentlessly pursuing excellence by:

  • purposefully developing a player and people-centered culture;
  • deeply connecting with our fans, partners, and colleagues;
  • passionately creating lifetime memories for generations of families and friends; and
  • meaningfully impacting our communities and the game of baseball.

At the Pirates, we believe in the power of a diverse workforce and strive to create an inclusive culture centered in Passion, Innovation, Respect, Accountability, Teamwork, Empathy, and Service.

Job Summary

As a Data Scientist on the Pirates Research & Development team, you will help transform a wealth of baseball data — from box scores and player tracking to video and biomechanics — into actionable insights that drive the Pirates to make better, faster acquisition, development, and deployment decisions. You will work closely with other data scientists, analysts, and software engineers across Baseball R&D as well as other stakeholders across Baseball Operations (scouts, coaches, player development, front office) to turn your statistical and machine learning models into actionable decision tools.

Responsibilities:

  1. Design, build, validate, and deploy statistical and/or machine-learning models to support all facets of baseball operations, including scouting, player acquisition, player development, and on-field decision making.
  2. Build tools, prototypes, and visualizations to translate complex data and model results into insights understandable by coaches, players, and decision-makers.
  3. Communicate results and insights clearly to both technical and non-technical audiences.
  4. Partner with data engineers to build scalable data pipelines and maintain data quality.
  5. Stay abreast of new data sources, analytical techniques, and research.
  6. Help the organization experiment, learn, and iterate.

Qualifications

We recognize that no candidate will meet every qualification listed below. If you are excited about this role and believe you can add value to our work, we encourage you to apply even if your experience does not align perfectly with every requirement.

Required:

  1. Degree (or equivalent experience) in a quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Economics, Machine Learning, Biomechanics, Engineering, Operations Research).
  2. Demonstrated experience applying complex statistical and/or machine learning tools to real-world problems.
  3. Demonstrated proficiency in a programming language such as Python or R for data analysis and modeling.
  4. Demonstrated ability to communicate complex quantitative concepts clearly, both written and verbally.
  5. Demonstrated experience collaborating with others on data science projects.
  6. Authorized to work lawfully in the United States.

Desired:

  1. Familiarity with advanced statistical techniques (e.g., fixed-effect / random-effect models, generalized additive models, Bayesian modeling, probabilistic programming).
  2. Experience with machine-learning / deep-learning frameworks (e.g., PyTorch, Tensorflow), especially applied to high-dimensional, spatiotemporal, or biomechanical data.
  3. Background in computer vision, biomechanics, sports-science, or modeling of dynamic physical systems.
  4. Prior experience in sports analytics context; baseball is a plus.
  5. Experience with database languages (e.g., SQL) and working with large / relational datasets.

Equal Opportunity Employer

The Pittsburgh Pirates are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status or any other characteristic protected by law.

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