ZipRecruiter

Log In

1

Sports Data Science Internship Jobs in Indiana (NOW HIRING)

The Nature Conservancy

NCS Data Scientist

Arlington, IN · On-site +1

... science syntheses. * Works across multiple geographies and timezones to provide technical and ... May lead staff, interns or volunteers on a project basis. * May manage a grant, contract or request ...

New

Michelin

Data Engineer

Woodburn, IN

$102K - $123K/yr

This can include internship, Co-op, apprentices, military service, or similar programs. * BS in Computer Engineering, Computer Science, Data Engineering, Data Scientist, or a technical degree, or ...

Michelin

Data Engineer

Woodburn, IN · On-site

$102K - $123K/yr

This can include internship, Co-op, apprentices, military service, or similar programs. * BS in Computer Engineering, Computer Science, Data Engineering, Data Scientist, or a technical degree, or ...

next page

Showing results 1-20

All JobsSports Data Science JobsSports Data Science Internship JobsSports Data Science Internship Jobs in Indiana

Sports Data Science Internship information

What is a Sports Data Science Internship?

A Sports Data Science Internship is a temporary position that allows students or recent graduates to gain hands-on experience applying data science techniques to sports-related problems. Interns typically work with data from games, athletes, or teams to analyze performance, develop predictive models, and support decision-making in sports organizations. This role often involves using programming languages like Python or R, working with large datasets, and collaborating with coaches or analysts. Interns may also assist in visualizing data and presenting insights to help improve team strategies or player development.

What are the key skills and qualifications needed to thrive as a Sports Data Science Intern, and why are they important?

To thrive as a Sports Data Science Intern, strong quantitative skills, a background in statistics or data science, and experience with sports analytics are generally required. Familiarity with programming languages such as Python or R, data visualization tools, and knowledge of sports data platforms or databases is typical. Strong problem-solving abilities, attention to detail, and effective communication help interns stand out in team settings. These skills are crucial for analyzing complex sports data, generating actionable insights, and effectively conveying findings to coaches and decision-makers.

What types of projects or tasks can I expect to work on during a Sports Data Science Internship?

As a Sports Data Science Intern, you can expect to work on projects such as analyzing player performance data, building predictive models for game outcomes, and cleaning large datasets for use in analytics. Interns often collaborate with data scientists, coaches, and performance analysts to translate raw data into actionable insights. You'll likely use programming languages like Python or R and get exposure to sports-specific analytics software, providing valuable hands-on experience that can help launch your career in sports analytics.

What is the difference between Sports Data Science Internship vs Sports Data Analyst?

AspectSports Data Science InternshipSports Data Analyst
Required CredentialsRelevant coursework, basic programming skillsDegree in statistics, data science, or related field
Work EnvironmentInternship programs, sports teams, analytics companiesFull-time roles in sports organizations, analytics firms
Employer & Industry UsageEntry-level, training-focused positions in sports analyticsProfessional, ongoing data analysis roles in sports

The Sports Data Science Internship is an entry-level, training-focused position designed for students or recent graduates gaining experience in sports analytics. In contrast, a Sports Data Analyst is a full-time professional role requiring more experience and specialized skills. Internships provide foundational exposure, while analysts handle ongoing data projects in sports organizations.

What are popular job titles related to Sports Data Science Internship jobs in Indiana? For Sports Data Science Internship jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Sports Data Science Internship jobs in Indiana look for? The top searched job categories for Sports Data Science Internship jobs in Indiana are:
What cities in Indiana are hiring for Sports Data Science Internship jobs? Cities in Indiana with the most Sports Data Science Internship job openings:
Sports Data Science Internship jobs near you
Infographic showing various Sports Data Science Internship job openings in Indiana as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Postdoctoral Fellow in Biostatistics and Health Data Science

Indiana University Academic Positions

Kokomo, IN

$42K - $58K/yr

Other

Re-posted 10 days ago

Job description

Position Details
Title Postdoctoral Fellow in Biostatistics and Health Data Science Specific Title Appointment Type Postdoctoral Fellow Department IUSM - Biostatistics Campus IU School of Medicine Indianapolis Position Summary
Postdoctoral Researcher to advance research at the intersection of artificial intelligence for healthcare, multimodal data analysis (EHRs, medical imaging, omics, physiological signals, clinical notes), and causal AI (causal inference, discovery, counterfactual reasoning). The successful candidate will collaborate with an interdisciplinary team of computer scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations.
Key responsibilities include:
  • Lead original research in multimodal and causal AI for health; design, implement, and rigorously evaluate algorithms and full pipelines.
  • Build reproducible research pipelines and maintain reliable experiment codebases (prefer Python).
  • Apply causal inference and discovery frameworks to clinical questions.
  • Translate proposed methods and frameworks into real-world clinical workflows.
  • Contribute to grant proposals and research reports.

This is an exciting opportunity to join a fast growing BHDS Department with 36 faculty members and more than 50 professional staff. We are dedicated to excellence in biostatistical, health data science, and informatics research and education. We have an extensive portfolio of research program in related areas. Our NIH funding as principal investigators and co-investigators has been ranked among the top in the nation. The Department currently has an ongoing PhD program in Biostatistics, MS program in Biostatistics, and BS program in Health Data Science.
We have established strong collaborations with both clinical and basic science research departments and divisions and health systems including IU Health and Eskenazi Hospitals as well as strong partnerships with major research institutes and centers including Regenstrief Institute, Center for Computational Biology and Bioinformatics, Indiana Clinical and Translational Science Institute (CTSI), Indiana University Simon Comprehensive Cancer Center, Indiana Institute of Biomedical Research, and Indiana Alzheimer's Disease Research Center. Additional details about the Department and the PhD program are available on our web page: https://medicine.iu.edu/biostatistics.
The Indianapolis Campus is the focal point of health professions education at Indiana University, and the School of Medicine is the country's second largest allopathic medical school. Indianapolis consistently ranks high nationally on many of the "best places to live" lists and has an economy that is growing in the life sciences arena. In addition, it has always been one of the cities with the lowest cost of living. Carmel, Indy's northern neighbor, was recently named as the best mid-sized city in the country.
IUSM is committed to being a welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all throughout the state of Indiana.
Indianapolis is the capital and most populous city in the State of Indiana. It is growing economically thanks to a strong corporate base anchored by the life sciences. Indiana is home to one of the largest concentrations of health sciences companies in the nation. Indianapolis has a sophisticated blend of charm and culture with a wonderful balance of business and leisure. The growing residential base is supported by rich amenities and quality of life - the city possesses a variety of professional sports, arts venues and outdoor recreation areas. Residents of this dynamic city, and surrounding suburbs, enjoy leading educational systems and top-ranked universities, paired with a diverse population. Indianapolis International Airport is a top-ranked international airport, being named "Best Airport in North America" by Airports Council International for many years. For additional information on life in Indy: https://faculty.medicine.iu.edu/relocation. The search will continue until the positions are filled. 


Basic Qualifications
Required Qualifications:
  • Ph.D. (by start date) in Computer Science, Biomedical Informatics, Health Data Science, Biostatistics, or a closely related area.
  • Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP.
  • Demonstrated working experience with healthcare data (e.g., EHR, clinical text, imaging, omics).
  • Proficiency in Python and ML tooling (e.g., PyTorch, scikit-learn), version control (Git), and experiment tracking (e.g., Weights & Biases).
  • Excellent written and oral communication skills, and ability to collaborate with multidisciplinary teams.
Preferred Qualifications:
  • Experience with LLMs/foundation models (e.g., clinical NLP, retrieval-augmented generation, instruction tuning) and multimodal transformers.
  • Solid understanding of causal methods (e.g., propensity scores, IPW, matching) and/or causal discovery.
  • Familiarity with data engineering and MLOps (e.g., SQL, Spark, Airflow, Docker, Kubernetes).
  • Knowledge of responsible/ethical AI for health: fairness/equity, interpretability, robustness, privacy (e.g., differential privacy, federated learning).
  • Track record of first-author publications in relevant venues and collaborative open-source contributions.

Department Contact for Questions
Professor Jiang Bian via email at: bianj@regenstrief.org
Additional Qualifications Special Instructions Priority Application Review Deadline Expected Start Date Posting Number IUSM-02286-2025

Apply