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Please note: A cover letter is required for consideration for this position and should be attached as the first page of your resume. Applications receiving serious consideration will include a cover letter that clearly addresses the applicant’s interest in the position and that specifically relates the skills and experience that are relevant to the required and desired qualifications described in this posting. 

Job Summary

The Detroit Metropolitan Area Communities Study (DMACS) is seeking a Research Area Specialist who will join a team of faculty and staff to provide data management, programming, analysis, and technical support to researchers. DMACS is a representative online panel survey of Detroit residents, fielding at least three survey waves a year. The successful candidate for this position will assist in cleaning, weighting, and analyzing the data from each of these surveys, preparing datasets for public use, offer guidance on data safeguarding, and be responsible for maintaining the database of panel respondents and the integration of the panel database with other programs such as Qualtrics or other data collection software.


The successful candidate for this position will use a mix of programming, statistical, and consulting skills to support DMACS in the production and release of high quality survey data and analysis.  

Responsibilities*

  • Writing, validating, and documenting statistical code in packages including Stata, and R that permits the cleaning, summarizing, and analysis of survey data. 
  • Writing, validating, and documenting computer code in statistical software packages, including Stata and R, for creation of survey weights and imputation of data necessary for weighting.
  • Preparing datasets for archiving and public release.
  • Integrating survey data with secondary data characterizing respondents’ geographic areas (e.g., from the U.S. Census and other administrative data sets).
  • Developing and maintaining an ongoing database of panel participants that integrates with Qualtrics and with email management software.
  • Supporting researchers with data analysis and visualization.
  • Consulting with DMACS team members on: 1) conducting statistical analyses, and 2) managing and safeguarding data.
  • Other duties as assigned.

Required Qualifications*

  • Master’s degree in information science, statistics, computational social science, or a relevant social science discipline, such as sociology, or economics and at least 2 years’ experience (in either a business or academic setting) working with large research data sets including data cleaning and management, and statistical analysis OR an equivalent combination of education and experience.
  • Previous experience consulting with clients on statistical analysis, data management, and computing.
  • Strong command of one or more of the following languages: R, Stata, and Python.
  • Strong computing skills, including experience with SQL programming and/or other relational database management, and the ability to learn new software packages quickly.
  • Demonstrated continuous development of programming and analytic skills.
  • Experience programming surveys in Qualtrics or other similar software.
  • Demonstrated creativity and flexibility in applying skills toward identifying and resolving data management and analysis issues.
  • Ability to effectively interact with individuals from diverse backgrounds, including the ability to work cooperatively with faculty and staff throughout the Ford School and the greater U of M community.
  • Ability to work independently and as a team member, set priorities and to adapt as priorities shift, to handle multiple assignments and deadlines, and to display excellent judgment, while operating in a flexible and professional manner.  
  • Ability to manage a large and diverse workload with attention to detail and the ability to meet deadlines in a timely manner.  
  • Excellent written and verbal interpersonal communication skills.

Desired Qualifications*

  • More than 5 years of prior experience with quantitative data analysis.
  • Experience with text analysis, machine learning, and/or data mining.
  • Experience working with restricted data and data safeguarding procedures.
  • Experience with GIS.
  • Experience with data visualization and presentation.
  • Supervisory or team management experience.
  • Experience providing instruction/training to others.

U-M EEO/AA Statement

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