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Data Analyst

Job in Miami, Miami-Dade County, Florida, 33146, USA
Listing for: University of Miami
Full Time, Seasonal/Temporary, Apprenticeship/Internship position
Listed on 2026-11-01
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst
  • Research/Development
    Data Scientist
Job Description & How to Apply Below
Position: Data Analyst 3
Current Employees:

If you are a current Staff, Faculty or Temporary employee at the University of Miami, please  to log in to Workday to use the internal application process. To learn how to apply for a faculty or staff position, please review this tip sheet.

The University of Miami’s Business School has an exciting opportunity for a full-time Data Analyst 3 to work on the Coral Gables campus.

Job Description

Title:

Data Analyst III Department:
Department of Health Management and Policy, University of Miami Business School Reports to Dr. Michael T. French, Professor and Chair of the Department of Health Management and Policy

Location:

Coral Gables, FL (in-person)
Training: A master’s or doctorate degree in economics, public policy, health policy, health services research, or a closely related field with graduate training in econometrics, completed by the start date

Start date:

As soon as possible, ideally by December 2026 and no later than January 2027

Job Summary The Data Analyst III will conduct applied empirical research in health economics, health services research, and health policy alongside research-active faculty in the Department of Health Management and Policy (HMP) at the University of Miami Business School. The work is primarily quantitative and spans the full research process: developing research questions and identification strategies, cleaning and analyzing data, implementing causal inference methods, producing tables and figures, and drafting sections of manuscripts for peer-reviewed journals and conference presentations.

We are seeking a candidate with strong training in econometrics and a genuine interest in academic research. Candidates should have experience implementing causal inference methods (e.g., difference-in-differences, instrumental variables, regression discontinuity) with a solid understanding of endogeneity and causal identification. Applicants whose training is primarily in data analytics, business analytics, or data science, without complementary graduate coursework in econometrics, are unlikely to be a good fit.

Beyond the requisite technical skills, the ideal candidate will bring professional maturity: the ability to take initiative, communicate proactively, exercise sound judgment with limited oversight, and contribute intellectually to the direction of the research.

This is a full-time research support position. The Data Analyst’s time is dedicated to faculty-led projects, with no protected time for independent research. Co-authorship opportunities on resulting manuscripts are at the discretion of the lead faculty member and are based on substantive intellectual contribution. The role is best suited to master’s- or PhD-trained candidates seeking a sustained career in applied research as part of a faculty-led team.

It is not a post-doctoral position, and candidates focused on building an independent research agenda are unlikely to find it a good fit.

To apply , please submit (1) a resume or CV, (2) unofficial graduate transcripts, (3) a list of three references with contact information, and (4) a cover letter of no more than two pages. The cover letter should describe your background and fit for the role, your interest in being based in Miami, and one causal inference analysis or similar project you have implemented, including the research question, the econometric method(s), and the statistical software program used.

Job Responsibilities Explore new datasets and propose potential research questions and identification strategies to faculty.

Contribute to study design and protocol development, including discussions of causal identification strategies, data requirements, and advanced analytic approaches.

Clean, manage, and analyze research datasets with limited…
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