Research Associate, Data Scientist, Research Assistant​/Associate

Research Associate

The Cecil G. Sheps Center for Health Services Research at UNC Chapel Hill seeks to improve the health of individuals, families, and populations by understanding the problems, issues, and alternatives in the design and delivery of health care services. This is accomplished through an interdisciplinary program of research, consultation, technical assistance, and training that focuses on timely and policy-relevant questions concerning the accessibility, adequacy, organization, cost, and effectiveness of health care services, and the dissemination of this information to policymakers and the general public.

The Sheps GME Technical Assistance Center at the Cecil G. Sheps Center is recruiting a Research Associate to provide quantitative data management and analysis support under the direction of Mukesh Adhikari, Research Investigator. This position will work across state and federally funded technical assistance centers and projects supporting the development of new medical and dental training programs in underserved communities to expand the health workforce.

The Research Associate will support a portfolio of applied research studies and data projects under the direction of the senior leadership and research personnel. Day-to-day work centers on the hands-on tasks that keep quantitative research moving: assembling data from primary and secondary sources; cleaning, managing, and documenting datasets; running statistical analyses as directed; and preparing tables, figures, and written summaries that support reports, findings briefs, and manuscripts.

The position carries out and applies analytic approaches under the principal investigator's direction.

Principal functions include: (a) collecting, cleaning, managing, and documenting research data; (b) conducting quantitative analyses using Excel, Stata, R, and/or Python under the direction of the principal investigator; (c) preparing tables, figures, and summaries that support reports, briefs, and manuscripts; (d) maintaining well-documented, reproducible analytic code and workflows; and (e) providing administrative and project-coordination support. The role is well suited to a detail-oriented analyst who is comfortable taking direction and committed to the recurring, behind-the-scenes data work that reliable research depends on.

Minimum Education and Experience Requirements - Master's or Bachelor's and 0-2 years' experience; or will accept a combination of related education and experience in substitution.

Required Qualifications , Competencies, and Experience
- * Demonstrated proficiency in at least one statistical programming language – Stata, R, and/or Python. Applicants with no evidence of Stata, R, and/or Python experience in their application materials will not be considered.
* Demonstrated experience across the full quantitative workflow, including data collection and assembly, data cleaning and management, and statistical analysis.
* Demonstrated experience preparing written research products such as reports, findings briefs, or manuscripts.
* Demonstrated ability to document analytic decisions, assumptions, and code so that work is transparent and reproducible.
* Strong attention to detail and the ability to manage multiple tasks and deadlines.
* Proactive, collaborative team orientation with strong interpersonal and written and oral communication skills.

Preferred Qualifications , Competencies, and Experience
- * Relevant post-Baccalaureate degree required in relevant field (e.g., economics, statistics, biostatistics, epidemiology, public policy, health policy and management, data science, or a closely related discipline); for candidates demonstrating comparable independent research productivity, will accept a relevant undergraduate degree and 3 or more years of relevant experience in substitution.
* Experience working with large secondary datasets (e.g., administrative, claims, survey, or publicly available data such as the Census/American Community Survey), including acquiring, merging, and managing data from multiple sources.
* Familiarity with Medicare Cost Report Data
* Some exposure to methods beyond standard regression (e.g., panel/longitudinal data or multilevel modeling) is a plus, but not required.
* Familiarity with causal inference approach (e.g., difference-in-differences) is welcome but not expected.
* Experience designing or conducting studies intended to inform policy.
* Experience with version control (e.g., Git) and reproducible research tools.
* Experience translating research results to academic, stakeholders, or policy audiences.
* Experience mentoring or supervising students or junior research assistants.
* Prior experience in an academic or applied research setting.