1

Sports Data Science Internship Jobs in Indiana (NOW HIRING)

... 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 ...

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 ...

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

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:
Infographic showing various Sports Data Science Internship job openings in Indiana as of August 2026, with employment types broken down into 13% Internship, 56% Full Time, 28% Part Time, and 3% Contract. Highlights an 97% In-person, and 3% Remote job distribution.

Postdoctoral Fellow in Biostatistics & Health Data Science

Indiana University School of Medicine

Indianapolis, IN • On-site, Remote

$46K - $63K/yr

Full-time

Re-posted 10 days ago


Job description

Postdoctoral Fellow in Biostatistics & Health Data Science

Indiana University is an equal opportunity employer and provider of ADA services and prohibits discrimination in hiring. See Indiana University's Notice of Non-Discrimination here which includes contact information.

The Annual Security and Fire Safety Report, containing policy statements, crime and fire statistics for all Indiana University campuses, is available online. You may also request a physical copy by emailing IU Public Safety at iups@iu.edu

The postdoctoral position addresses a fundamental and timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization?

We are particularly interested in:

  • LLM-driven systems for aligning real-world health data to standards like OMOPCDM, FHIR, and UMLS
  • Agent-based workflows that explain, refine, and adapt semantic mappings over time
  • Hybrid architectures that combine knowledge-grounded reasoning with flexible machine learning
  • Tools that reduce manual burden while preserving traceability and clinical interpretability

This position offers the opportunity to publish novel methods, work with real messy multi-source data, and contribute to infrastructure supporting population-level research and health equity.

The postdoctoral fellow will be based in the Department of Biostatistics and Health Data Science at Indiana University School of Medicine, in close collaboration with the Regenstrief Institute, a nationally renowned center for health informatics research and real-world data infrastructure.

Our Team's Approach-We are not a pure research group. We operate at the interface of research and health data operations, building methods that not only publish but also deploy. We handle real clinical and public health data problems where ambiguity, variation, and scale are the norm—not the exception.

We welcome postdocs who want to drive innovation while engaging deeply with practical, meaningful data challenges.

Responsibilities:

  • Design and implement LLM-based methods for clinical data harmonization, semantic normalization, and ontology alignment
  • Develop multi-agent or RAG-style (retrieval-augmented generation) workflows for schema matching and terminology mapping
  • Collaborate with national and multi-institutional initiatives in data integration and standardization
  • Support open-source tooling, reproducible pipelines, and standards-based approaches (e.g., OMOP, FHIR, UMLS)
  • Lead or support manuscript preparation and dissemination at top informatics and AI venues
  • Contribute to grant development and proposal writing

What We Offer:

  • A collaborative environment at the intersection of real-world data, applied AI, and translational science
  • Opportunities to work across academic, clinical, and public health settings
  • Mentorship and support toward independent research or career development in academia or industry
  • Competitive salary and benefits through Indiana University
  • A culture that values both scientific innovation and practical impact

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.

Department Contact for Questions - Professor Jiang Bian via email at: bianj@regenstrief.org

Additional Qualifications - Preferred Qualifications:

  • Experience with concept normalization, ontology mapping, or schema alignment
  • Familiarity with LLM agents, tool-augmented reasoning, or hybrid rules + LLM systems
  • Record of publications in relevant domains (informatics, machine learning, AI, knowledge representation)
  • Experience with multi-site data harmonization or federated data environments

Special Instructions

Priority Application Review Deadline

Expected Start Date

Posting Number - IUSM-02358-2026

Supplemental Questions

Required fields are indicated with an asterisk (*).

  • * How did you hear about this position?
    • Personal Contact: At Professional Meeting or Conference
    • Personal Contact: Direct Contact by Search Committee
    • Personal Contact: Referred by colleague or advisor
    • Personal Contact: School of Medicine recruiter
    • Personal Contact: IUHP Physician Recruiter
    • Announcement: Other Journal or Magazine
    • Announcement: Other Website
  • * Are you a dual career partner (your partner or spouse is already being recruited)?
    • Yes
    • No

Applicant Documents

Required Documents

  • Curriculum Vitae
  • Letter of Application
  • List Of References

Optional Documents