Health Research Data Specialist

University Of Michigan; Ann Arbor (MI); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid or remote work options

Job summary

The University of Michigan is seeking a Research Health Data Specialist within the AI & Digital Health Innovation (AI&DHI) initiative. You will support investigators by translating questions into data strategies, building documentation for cohorts, and enabling reproducible research across campus.

You will collaborate with the Data & AI Solutions team to ensure data resources meet scientific goals while adhering to governance, IRB, and privacy requirements.

Qualifications

• Doctoral degree in information science, data science, public health, computer science, biostatistics, epidemiology, or a related field.
• Master’s degree with relevant experience may be considered.
• Experience with data management, workflow design, and research data governance.
• Experience with IRB processes, human subjects research, and HIPAA compliance.
• Strong project management and organizational skills.
• 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 data sources, interpret data structures, and design studies.
• Connect investigators with health datasets, tools, technologies, and workflows to accelerate research.
• Consult on study planning and research workflows to enable reproducible, fundable research outcomes.
• Identify barriers and bottlenecks around data to improve research workflows and access.
• Ensure data access and activities align with IRBMED, HIPAA, and governance requirements.
• Stay current with digital health, biomedical informatics, and data science methods.

Skills

Data management

Workflow design

Research data governance

Project management

Scientific writing

IRB/HIPAA compliance

Interdisciplinary collaboration

Communication skills

Education

Doctoral degree in information science, data science, public health, computer science, biostatistics, epidemiology, or a related field

Master’s degree with relevant experience (considered)

Tools

R

Python

GitHub

Job description

A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.

Job Summary

The Research Health Data Specialist is a key member of the AI & Digital Health Innovation (AI&DHI) initiative at the University of Michigan, working within the Data & AI Solutions team and collaborating with partners across campus. This role is designed to maximize research output by helping investigators translate scientific questions into actionable data strategies, building a data documentation system that supports rigorous, reproducible, and scalable research, and enabling efficient access to high-value datasets. A central expectation of this role is the ability to integrate scientific expertise and methodological insight into consultations, enabling research projects to progress smoothly and produce high-quality publications, grant submissions, and digital health innovations. The interview process will include a research presentation that should demonstrate your ability to bridge scientific questions, health data resources, and operational execution to achieve a meaningful research outcome. While this role in our team won't directly participate in research studies, familiarity with conducting scientific research is required to fulfill the responsibilities of the role.

Responsibilities*

Core Responsibilities

Scientific Research Facilitation

• 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.

Data Documentation

• 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.

Required 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.

Desired Qualifications*

Experience with workflow automation, high-throughput computing, or cloud/HPC environments.

• Experience with GitHub and documentation
• Proficiency with R, Python, or similar tools for data handling.
• Experience with AI and LLMs, including familiarity with model development, evaluation, and deployment in research settings.

Experience training researchers or students.

Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes .

Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third-party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Reporting Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.

Application Deadline

Job openings are posted for a minimum of seven calendar days.The review and selection process maybegin as early as the eighth day after posting.Thisopening may be removed from posting boards and filled any time after the minimum posting period has ended.

U-M EEO Statement

The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.