Research Health Data Strategist

Michigan Medicine; Ann Arbor (MI); Hybrid; USD 90,000 - 120,000; Full time

Job summary

University of Michigan's AI & Digital Health Innovation initiative seeks a Research Health Data Specialist to translate scientific questions into data strategies and build a robust data documentation system for reproducible research. You will enable investigators to access high-value datasets, design scalable data workflows, and support publications and grants.

You will collaborate with the Data & AI Solutions team to develop innovative data solutions that advance digital health research while

Qualifications

• Doctoral degree in information science, data science, public health, computer science, biostatistics, epidemiology, or a related field.
• Exceptional candidates with a Master’s degree and relevant experience may be considered.
• Experience with data management, workflow design, and research data governance.
• Experience working with large, complex datasets (clinical, digital health, sensor, EHR, socioeconomic, genomic, etc.).
• Strong project management and organizational skills.
• Experience with IRB processes, human subjects research, and HIPAA compliance.
• Demonstrated ability to support research that leads to publications, grant submissions, or other high-impact deliverables.
• Excellent scientific writing and communication skills.
• Enthusiasm for digital health, AI, and interdisciplinary scientific research.

Responsibilities

• Apply scientific expertise to help investigators refine hypotheses, select appropriate data sources, interpret data structures, understand methodological constraints, and design studies that maximize scientific impact.
• Connect investigators with the appropriate health datasets, tools, technologies, and workflows to accelerate research and publication-ready results.
• Consult on study planning and research workflows to enable publishable, fundable, reproducible, and scalable research outcomes.
• Proactively identify barriers, bottlenecks, and opportunities around data to improve research workflows and data accessibility.
• Ensure data access and research activities align with IRBMED, HIPAA, and AI&DHI governance requirements, including support for IRBMED submissions to minimize delays.
• Stay current with digital health, biomedical informatics, and data science methods and literature to ensure consultations reflect state-of-the-art approaches.
• Collaborate with the Data & AI Solutions team to develop and promote innovative data solutions that improve the quality, reproducibility, efficiency, and impact of research across AI&DHI.
• Create study cohorts and computed concepts by defining inclusion/exclusion criteria, extracting relevant data elements, validating cohort integrity, and ensuring cohorts align with scientific aims and regulatory requirements.
• Develop, augment, and maintain comprehensive documentation for available cohorts, data, and resources.
• Organize health data resources into repositories (e.g., GitHub) to support transparency and reproducibility.
• Collaborate with technical teams to ensure data resources and tools align with scientific goals and support robust research outputs.

Skills

Data governance

Project management

Scientific writing

Communication skills

IRB processes

HIPAA compliance

Data integration

Clinical data experience

Education

Doctoral degree

Master's degree with relevant experience

Tools

Python

R

SQL

GitHub

Job description

University of Michigan's AI & Digital Health Innovation initiative seeks a Research Health Data Specialist to translate scientific questions into data strategies and build a robust data documentation system for reproducible research. You will enable investigators to access high-value datasets, design scalable data workflows, and support publications and grants.

You will collaborate with the Data & AI Solutions team to develop innovative data solutions that advance digital health research while