Health Data Science/AI Associate

Regenstrief Institute, Inc.•Indianapolis, IN

1d•Hybrid

About The Position

Working alongside experienced data engineers, analysts, investigators, and scientists, associates contribute directly to meaningful research projects while developing technical expertise, professional skills, and an understanding of modern health data science. Projects are selected to align with each extern's strengths, interests, and career goals while providing opportunities to expand knowledge across cloud computing, AI, data engineering, clinical data analysis, and health informatics. New graduates and early-career professionals are strongly encouraged to apply. Prior professional experience is welcomed but not required. This is a six-month role, with the possibility to extend to a second six-month period. This position is a hybrid position with at least one (1) to two (2) days of onsite activity based on business needs. This position is located in downtown Indianapolis IN.

Requirements

Requires at least a Bachelor's degree in Data Science, Health or Biomedical Informatics, Computer Science, Data Engineering, Statistics, Information Science, Applied Mathematics, or a related quantitative discipline.
Coursework, academic research, internships, or project experience involving programming, data analysis, AI, or data science.
Basic proficiency with SQL, Python, or another programming language.
Demonstrated analytical thinking and problem-solving skills.
Strong written and verbal communication skills.
Ability to collaborate effectively with mentors, scientists, engineers, analysts, and project teams.
Ability to prepare technical documentation and communicate technical concepts clearly.
Intellectual curiosity, initiative, and willingness to learn new technologies.
Commitment to protecting confidential and sensitive health information.

Nice To Haves

Cloud computing platforms
Machine learning or artificial intelligence
Clinical or healthcare data
Data visualization tools
Git or source code management
Health data standards such as OMOP, HL7, or FHIR

Responsibilities

Participate as an active member of multidisciplinary project teams supporting health research initiatives.
Assist with the engineering, preparation, transformation, and analysis of large clinical and administrative datasets.
Develop and maintain SQL and Python code to support data extraction, integration, quality improvement, and analytics.
Contribute to cloud-based data engineering initiatives supporting AI-ready infrastructure.
Assist in implementing and improving data pipelines, workflows, and automated processes.
Support the development, evaluation, and responsible use of AI-enabled tools that improve research and operational efficiency.
Work with health data standards and common data models, including concepts such as OMOP and HL7/FHIR.
Participate in data validation, quality assurance, and documentation activities to ensure reproducibility and integrity.
Prepare technical documentation, process documentation, and project summaries.
Present project updates and findings to mentors, supervisors, and project teams.
Participate in team meetings, knowledge-sharing activities, and professional development opportunities.
Demonstrate appropriate stewardship of sensitive health information while adhering to security, privacy, and compliance requirements.
Perform other related duties as assigned.