Statistician Senior / Intermediate (Hybrid)

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The Wearables In Reducing Risk and Enhancing Daily Lifestyle (WIRED-L) Research Center is an American Heart Association-funded research center within the University of Michigan Department of Internal Medicine focused on the intersection of health and technology, with specific interest in digital health and health equity research. This position will lead data analysis for the center’s research projects, including two actively enrolling digital clinical trials under the direction of a multidisciplinary group of researchers.

Mission Statement

Michigan Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally.  Our mission is guided by our Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society.


This position involves a wide range of tasks including programming and data analysis to support two ongoing clinical digital clinical trials with the potential for involvement in multiple upcoming trials evaluating digital interventions across a range of health conditions. Analyses will need to integrate high-dimensional digital data from smartphones and other wearable devices with electronic medical record and survey data to understand participants’ health and treatment response. Some of the work will involve observational data analyses while other work will involve clinical trial data. This position will partner closely with the Center’s data architect to ensure setup, flow, and analysis of study data generated by the Center’s research projects.

  • Contributing to study design decisions
  • Performing power calculations and estimating sample size
  • Writing, testing, and implementing programs using SAS/STATA/R/Python to clean, manage, merge, and analyze large, complex datasets
  • Implementing methods to ensure data quality
  • Supporting PIs and others in development of specific analysis plans
  • Independently conducting appropriate data analyses
  • Preparing and maintaining technical documentation of data and analytic files
  • Summarizing, interpreting, and presenting results in written, tabular and visual formats
  • Collaborate with team members in co-authoring manuscripts, presentations, abstracts, and grant proposals
  • Participating as a team member in discussions on analysis and improvement of data collection, quality of data analyses, programming and documentation.

Required Qualifications*

  • Bachelor's degree in statistics, mathematics, economics, biostatistics, computer science, information, or related field.
  • Experience with statistical programming language (e.g., SAS/STATA/R/Python) and SQL
  • Strong statistical background and programming knowledge.
  • Ability to be consistently detail-oriented.
  • Ability to draft statistical tests in accordance with project designs, solve analytic problems, and develop instruments and related analysis plans.
  • Working knowledge of epidemiologic concepts and methodology.
  • Experience with complex data structures and linkages between data sources.
  • Strong interpersonal and written communication skills. Proven ability to write clear and concise technical documentation, summaries of various methodologies, and descriptions of statistical results. Excellent communication and interpersonal skills are essential
  • Ability to prioritize, organize, and efficiently work on multiple projects at the same time.
  • Flexibility and ability to work independently and collaboratively with multiple researchers.

Senior Level: 3-5 years of professional experience

Intermediate Level: 1-3 years of professional experience

Desired Qualifications*

  • Masters/PhD preferred.
  • Direct experience in supporting, managing and analyzing major research projects using large datasets (e.g., clinical trials, clinical registries, Medicare, Medicaid, or commercial insurance).
  • Conversant or some knowledge of any of the following methodologies:  Logistic and OLS regression, propensity score matching or weighting, interrupted time series, difference-in-difference analysis, survival models, and cluster analysis. 
  • Interest in developing skills in machine learning and Artificial Intelligence tools
  • Teaching orientation and interest or experience in communicating and sharing programming and statistical approaches with colleagues and other internal partners.
  • Prior research publications in statistical or medical journals.
  • Experience with SQL including the ability to write update, select, insert, and join commands.

Work Schedule

This position is hybrid flexible, with an initial fully-remote option available depending on candidates’ availability and experience. Work schedule is tentatively standard 9-5, with additional flexibility depending on need.

Underfill Statement

This position may be underfilled at a lower classification depending on the qualifications of the selected candidate.

Background Screening

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 Report 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 may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.

U-M EEO/AA Statement

The University of Michigan is an equal opportunity/affirmative action employer.

U-M COVID-19 Vaccination Policy

COVID-19 vaccinations, including one booster when eligible, are required for all University of Michigan students, faculty and staff across all campuses, including Michigan Medicine.  This includes those working remotely and temporary workers.   More information on this new policy is available on the U-M Health Response website or the UM-Dearborn and UM-Flint websites.