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Intern Baseball Data Science Jobs in Philadelphia, PA

Athenago

Data Science Intern

Wilmington, DE

Role Overview The Data Science Intern will help us to understand the performance of Executive Partners (XPs) and build advanced matching models to evaluate Athena's Executive Partners (XPs) and ...

Campbell Soup Company

Data Science Intern

Camden, NJ · On-site

$15.25 - $20.25/hr

Since 1869, we've connected people through food they love. We're proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell's brand, as well as Cape Cod ...

Campbell's

Data Science Intern

Camden, NJ · On-site

$15.25 - $20.25/hr

Since 1869, we've connected people through food they love. We're proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell's brand, as well as Cape Cod ...

Campbell's

Data Science Intern

Camden, NJ · On-site

$15.25 - $20.25/hr

Since 1869, we've connected people through food they love. We're proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell's brand, as well as Cape Cod ...

Campbell Soup Company

Data Science Intern

Camden, NJ · On-site

$15.25 - $20.25/hr

Since 1869, we've connected people through food they love. We're proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell's brand, as well as Cape Cod ...

Ricoh USA, Inc.

Intern, Finance IT

Exton, PA · On-site

$17.25 - $22.50/hr

Finance IT Intern Position Profile The Intern will gain hands-on work experience by participating ... Supply Chain, Data Science, or similar). * Cumulative GPA of 3.0 or higher. * Ability to ...

Ricoh USA, Inc.

Intern, Finance IT

Exton, PA · On-site

$17.25 - $22.50/hr

Finance IT Intern Position Profile The Intern will gain hands-on work experience by participating ... Supply Chain, Data Science, or similar). * Cumulative GPA of 3.0 or higher. * Ability to ...

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All JobsIntern Baseball Data Science JobsIntern Baseball Data Science Jobs in Philadelphia, PA

Intern Baseball Data Science information

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How much do intern baseball data science jobs pay per hour?

As of Aug 27, 2026, the average hourly pay for intern baseball data science in Philadelphia, PA is $17.19, according to ZipRecruiter salary data. Most workers in this role earn between $14.57 and $19.42 per hour, depending on experience, location, and employer.

What is an intern baseball data science?

An Intern Baseball Data Science is a temporary position, usually for students or recent graduates, where the intern assists professional baseball organizations in analyzing game and player data. The role typically involves working with large datasets, using statistical methods and programming languages like Python or R to uncover insights that can improve team performance or strategy. Interns may help with data collection, cleaning, and visualization, and often collaborate with coaches, scouts, and analysts. This position is designed to provide hands-on experience in sports analytics and prepare interns for a potential career in data science within the sports industry.

What do interns in baseball data science do?

As an Intern in Baseball Data Science, you can expect to work on a variety of projects such as analyzing player performance data, building predictive models for game outcomes, and assisting with the visualization of statistical insights for coaches and scouts. Interns often clean and organize large datasets, contribute to ongoing research, and collaborate closely with data scientists, analysts, and baseball operations staff. This hands-on experience not only builds technical and analytical skills but also provides exposure to how data-driven decisions are made in a professional sports environment.

What skills and qualifications are needed to thrive as an intern in baseball data science?

To thrive as an Intern in Baseball Data Science, you need a strong background in statistics, data analysis, and programming, often supported by coursework in mathematics, computer science, or a related field. Familiarity with tools such as Python or R, SQL databases, and data visualization platforms like Tableau is typically required. Strong problem-solving abilities, attention to detail, and effective communication make candidates stand out in this position. These skills and qualities are essential for accurately analyzing player and game data, providing actionable insights, and contributing to team decision-making.

What is the difference between Intern Baseball Data Science vs Intern Sports Data Analysis?

AspectIntern Baseball Data ScienceIntern Sports Data Analysis
Required CredentialsRelevant coursework in data science, basic programming skills, knowledge of baseball statisticsCoursework in sports analytics, data analysis, programming, and sports management
Work EnvironmentBaseball teams, sports analytics firms, or sports media companiesSports organizations, media outlets, or analytics firms covering various sports
Industry UsageFocused on baseball-specific data, player performance, game strategiesBroader sports data, including multiple sports types and general performance metrics

Intern Baseball Data Science primarily concentrates on baseball-specific data analysis, requiring knowledge of baseball statistics and programming. In contrast, Intern Sports Data Analysis covers multiple sports, emphasizing broader data skills across various athletic disciplines. Both roles involve working in sports environments but differ in scope and specialization.

What are popular job titles related to Intern Baseball Data Science jobs in Philadelphia, PA?

For Intern Baseball Data Science jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Intern Baseball Data Science jobs in Philadelphia, PA look for?

The top searched job categories for Intern Baseball Data Science jobs in Philadelphia, PA are:

What cities near Philadelphia, PA are hiring for Intern Baseball Data Science jobs?

Cities near Philadelphia, PA with the most Intern Baseball Data Science job openings:

Intern Baseball Data Science jobs near you
Infographic showing various Intern Baseball Data Science job openings in Philadelphia, PA as of August 2026, with employment types broken down into 11% Internship, 73% Full Time, and 16% Part Time. Highlights an 65% In-person, 23% Hybrid, and 12% Remote job distribution, with an average salary of $35,758 per year, or $17.2 per hour.

Quantitative Analyst Associate (2027)

Philadelphia Phillies - Baseball Operations

Philadelphia, PA • On-site

Part-time

Posted 17 days ago

Job description

Title: Quantitative Analyst Associate
Department: Baseball Research & Development
Reports to: Lead/Senior Quantitative Analyst
Status: Hourly Part-Time Seasonal
Position Overview:
As a Quantitative Analyst (QA) Associate, you help shape The Phillies Baseball Operations strategies by processing, analyzing, and interpreting large and complex data. You do more than just crunch the numbers; you carefully plan the design of your own studies by asking and answering the right questions, while also working collaboratively with other analysts and software engineers on larger projects.
Using analytical rigor, you work with your team as you mine through data and see opportunities for The Phillies to improve. After communicating the results of your studies and experiments to Baseball Operations leadership and executive staff, you collaborate with front office executives, scouts, coaches, and trainers to incorporate your findings into Phillies practices. Identifying the challenge is only half the job; you also work to figure out and implement the solution.
Responsibilities:
  • Conduct statistical research projects and manage the integration of their outputs into our proprietary tools and applications (e.g., performance projections, player valuations, draft assessments, injury analyses, etc.)
  • Communicate with front office executives, scouts, coaches, and medical staff to design and interpret statistical studies
  • Assist the rest of the QA team with their projects by providing guidance and feedback on your areas of expertise within baseball, statistics, data visualization, and programming
  • Continually enhance your knowledge of baseball and data science through reading, research, and discussion with your teammates and the rest of the front office
  • Provide input to database architecture to ensure efficient application of baseball data

Required Qualifications:
  • Deep understanding of statistics, including supervised and unsupervised learning, regularization, model assessment and selection, model inference and averaging, ensemble methods, etc.
  • Meaningful experience programming, using analytical software (Python, R, or similar), and interacting with databases
  • Proven willingness to both teach others and learn new techniques
  • Willingness to work as part of a team on complex projects
  • Proven leadership and self-direction

Preferred Qualifications:
  • Possess or are pursuing a BS, MS or PhD in Statistics or related (e.g., mathematics, physics, or ops research) or equivalent practical experience
  • 0-5+ years of relevant work experience
  • Experience drawing conclusions from data, communicating those conclusions to decision makers, and recommending actions

To be considered, all candidates must submit a response for the prompt below:
In player evaluation, some metrics are highly predictive of future performance but provide limited information about why a player will succeed or fail. Other metrics may be less predictive on their own but can help identify specific strengths, weaknesses, or opportunities for improvement.
Assume you have access to several years of professional baseball data, including traditional statistics, pitch- or play-level tracking data, scouting evaluations, player demographics, injury history, and minor-league level and park context.
In 250 words or less, describe how you would determine which information should be included in a player projection model and which information should instead be used primarily to explain, diagnose, or contextualize the projection. Discuss how you would evaluate a metric that improves historical model accuracy but may not remain stable over time, may duplicate information contained in other variables, or may be difficult to obtain consistently for all players.
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital or veteran status, or any other protected class.

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