Research Scientist - Data Science, AI & Digital Health

This fifthlevel Research Professional serves as a senior individual contributor and recognized content expert in data science, artificial intelligence and digital health research. The position independently leads and advises on highly complex, systemlevel research projects and portfolios, working with faculty leaders with particular emphasis on aligning study design, analytic strategy, and realworld research operations.

The role functions as a strategic and methodological partner to faculty investigators, providing advanced guidance on when, how, and why data science and digital health methods should be applied-rather than serving as a primary analyst or system implementer. The incumbent integrates across disciplines and roles to translate research aims into executable, datadriven studies that advance learning health system sciences, working under general supervision with the authority to make daily operations decisions., 35%: Data Science & Digital Health Expertise

• Apply advanced data science, computational modeling, and digital health knowledge to shape research questions, hypotheses, and analytic approaches, rather than executing routine analyses.
• Evaluate appropriateness, strengths, and limitations of analytic methods, data sources, and digital tools in relation to study aims and operational constraints.
• Interpret analytic outputs in scientific and operational context, translating results into insights and recommendations for investigators and stakeholders.
• Leverage, rather than replicate, and coordinate the work of biostatisticians, analysts, and informatics staff and faculty.
• Contribute substantively to grant applications and manuscripts as a methodological and design coauthor.

25%: Bridging Study Design and Study Operations

• Serve as the primary integrator between faculty vision and operational execution for dataenabled studies. Lead integration of data science and digital health considerations into study design at the concept, proposal, and protocol stages.
• Advise faculty on tradeoffs among rigor, feasibility, scalability, and resource requirements in realworld research environments.
• Ensure coherence among research questions, data availability, analytic plans, and implementation workflows. Anticipate and resolve mismatches between protocol intent and daytoday research operations.
• Collaborate with study staff, analysts, informatics teams, and health system partners to operationalize complex designs.
• Guide development of reusable workflows and approaches that support multiple studies.
• Support project management primarily or working collaboratively with staff.

15%: People Management

• Provide leadership for staff and foster a professional, diverse and equitable working environment within the center for people from all backgrounds, communities, and identities, where staff are empowered and accountable.
• Directly oversee and manage CLHSS data scientists (2), who will be matrixed to assigned research projects based on skills and expertise, to meet defined project deliverables.
• Develop staff capacity and set goals aligned with overall center strategies.

15%: Strategic Consultation & Portfolio Leadership

• Provide consultative expertise to CLHSS leadership, faculty, and project teams on data science and digital health strategy.
• Shape the Center's approach to dataenabled research by identifying emerging methods, technologies, infrastructure needs, as well as grants and other funding opportunities.
• Influence research direction and quality across data science portfolio (multiple concurrent projects) without formal supervisory authority.
• Represent CLHSS as a subjectmatter expert in institutional and crossunit initiatives.
• Galvanize engagement with data science staff and faculty collaborators through varied approaches to build a pool of expertise supporting active projects, incubation of ideas, and joint pursuit of funding.

10%: Communication, Reporting & Knowledge Translation

• Produce highlevel reports, presentations, and guidance documents addressing complex technical and methodological issues.
• Communicate effectively with both technical and nontechnical stakeholders.
• Support dissemination of findings through scholarly publications and presentations.

• Advanced degree (Master's or higher) in a relevant field (e.g., data science, informatics, public health, biostatistics, or related) with one or more years of research training
• Progressively responsible experience (typically 4+ years) contributing to complex, datadriven health research in academic, clinical, or learning health system environments.
• Demonstrated expertise in applying data science to inform study design, analytic strategy, and research decisionmaking (e.g., realworld data, computational modeling, EHRbased research, digital tools).
• Experience running data or technology projects of moderate or significant complexity for at least 2 or more years.
• Proven ability to independently lead or influence highly complex research efforts, exercising sound judgment in ambiguous and evolving situations.
• Experience integrating study design with realworld research operations and data environments.
• Strong understanding of health data sources (e.g., EHR, registries, digital health data).
• Demonstrated ability to serve as a consultative partner to faculty and crossdisciplinary teams.
• Track record of scholarly contributions (e.g., grants, protocols, publications). Familiarity with the full research cycle.
• Excellent communication skills, with the ability to translate complex technical and methodological concepts into clear guidance for diverse audiences.

Preferred Qualifications:

• Doctoral degree (PhD, DrPH, ScD, or equivalent) in a relevant field.
• Experience in learning health system research, pragmatic clinical trials, implementation science, or embedded research within healthcare delivery systems.
• Demonstrated success contributing to or securing extramural funding (e.g., NIH, AHRQ, PCORI, foundations), particularly in dataenabled or digitally enabled research.
• Experience working across interdisciplinary teams, including collaboration with biostatisticians, informatics professionals, clinicians, and research operations staff.
• Familiarity with advanced analytic approaches (e.g., machine learning, causal inference, simulation modeling) sufficient to guide method selection and interpretation, even if not the primary analyst.
• Experience guiding development of reusable research infrastructure, such as data pipelines, workflows, or standardized methods across multiple studies.
• Experience mentoring or advising research staff or junior investigators in a nonsupervisory capacity.
• Knowledge of regulatory, ethical, and data governance considerations relevant to health data and digital research.

Committed to innovation and diversity, the Medical School educates physicians, scientists, and health professionals; generates knowledge and treatments; and cares for patients and communities with compassion and respect. We value excellence, inclusiveness, collaboration, and discovery.

The mission of the regional campus located in Duluth is to be a national leader in improving healthcare access and outcomes in rural Minnesota and American Indian/Alaska Native (AI/AN) communities. In partnership with CentraCare, the regional campus in St. Cloud offers a wide range of patient experiences throughout students' education in Greater Minnesota and prepares them to become exceptional clinicians and leaders for rural and immigrant populations.

Founded in 1888, the University of Minnesota Medical School has three campuses. A four-year MD program and the MD/PhD program are located on the Twin Cities campus in addition to MD programs at regional campuses in Duluth and St. Cloud. Pay and Benefits

Pay Range: $122,000 - $138,000; depending on education/qualifications/experience

Time Appointment: 100% Appointment

Work Location: Hybrid; 20% in person

Position Type: Faculty and P&A Staff

Please visit the Office of Human Resources website for more information regarding benefit eligibility.

The University offers a comprehensive benefits package that includes:

• Competitive wages, paid holidays, and generous time off
• Continuous learning opportunities through professional training and degree-seeking programs supported by the Regents Tuition Benefit Program
• Low-cost medical, dental, and pharmacy plans
• Healthcare and dependent care flexible spending accounts
• University HSA contributions
• Disability and employer-paid life insurance
• Employee wellbeing program
• Excellent retirement plans with employer contribution
• Public Service Loan Forgiveness (PSLF) opportunity
• Financial counseling services
• Employee Assistance Program with eight sessions of counseling at no cost

While our salary ranges provide a framework, it is important to note that most of the time, the initial pay may not reach the maximum of the range. This approach ensures that compensation reflects the value and unique contributions of each candidate while maintaining equity within our organization. As part of our commitment to fair and equitable compensation, please be aware that the salary offered to incoming candidates will be based on their individual credentials and experience.

The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds. The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment. About University of Minnesota The University of Minnesota, Twin Cities (UMTC) The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation's most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations. At the University of Minnesota, we are proud to be recognized by Forbes as a Best Employer for Company Culture (2026), Best Employer for Women (2023), and Best Employer by State (2022-2026). In 2026, we also received Culture Excellence & Industry Awards recognition for employee appreciation and work-life flexibility.