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A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should include salary requirements, address your specific interest in the position, and outline skills and experience that directly relate to this position.

Job Summary

The University of Michigan is seeking a data scientist to oversee data collection, analysis, modeling, and inference in the Office of Academic Innovation (AI). AI’s mission is to design, build, and research cutting-edge pedagogies, technologies, and experiences to drive the future of education. All of our work relies on inferences drawn from data: our success will be determined in large part by the quality of our data science team. This position will report to the Associate Director, Research & Development.


You are passionate about working closely with innovators from across the University of Michigan’s body of world class students, faculty, and staff. You love learning and are interested in an environment that provides the opportunity to work directly with world leaders in data science, causal inference, and education research, creating learning experiences and technologies which will transform higher education for the 21st century.


The Office of Academic Innovation is a strategic priority for the University of Michigan. Through curricular innovation, leadership in learning analytics and personalization at scale, AI aims to shape the future of learning and redefine public residential education at a 21st century research university by unlocking new opportunities for the U-M community and learners around the world.

Our preferred future includes:

  • An open model for pre-college learning and preparation that broadens access and enhances participation
  • A personalized, rigorous, and inclusive model for residential learning grounded in learning analytics and experimentation
  • A flexible and networked model for global and lifelong learning that embraces the evolution of a more permeable university
  • A participatory and inclusive model for public engagement that accelerates bilateral knowledge construction and sharing

As we reimagine the global public research university and create a culture of innovation in learning, we value:

  • boldness and humility
  • creativity and process
  • risk taking and tradition
  • personalization and scaleopenness

For more information, please visit our website: Academic Innovation.


  • Gather, analyze and interpret data from various sources that will suggest conclusions and support decision-making in AI products.
  • Work with project teams to use data analysis to inform the design and development of digital applications and online learning experiences that facilitate engaged and personalized learning experiences
  • Create user-friendly data visualizations that are effective in increasing awareness of initiative progresses across the office.
  • Enhance internal research capabilities within AI to leverage research findings for both application development and learning experience design.
  • Apply the best available techniques to the task of drawing inferences from data.
  • Manage data: inspect, clean, and transform data. Run database queries and provide datasets to AI team members and partners.
  • Maintain large data sets: merge files, restructure and recode variables, assign labels and values, check for errors, create codebooks, etc.
  • Develop, streamline, error-proof, and automate processes for managing data and producing reports.
  • Prepare and present reports and findings to teammates, faculty innovators, and advisory boards.
  • Act as a liaison between AI and various research partners and advisory boards. 

Required Qualifications*

  • A bachelor's degree in data science, statistics, informatics, econometrics, or a recognized field of science directly related to the data science tasks required for this position.
  • Significant experience with using either R or python to conduct statistical analyses.
  • Knowledge of, and experience with, various statistical analysis techniques, such as analyses of variance, factor analysis, reliability analyses, natural language processing, statistical processes control, linear and hierarchical modeling, etc.
  • Demonstrated ability to be self-directed and work independently or as part of a multicultural and collaborative environment.
  • Demonstrated ability to be flexible and work well in an environment with rapidly changing requirements and priorities.
  • Excellent communication skills and ability to collaborate with various faculty and members of a comprehensive team.
  • Experience working in a multidisciplinary, research-oriented environment.
  • Experience explaining data visualizations and statistical descriptors to audiences who are both unfamiliar and extremely familiar with statistics and data science.
  • Strong attention to detail.
  • An innovative nature and a desire to find better and more efficient ways of streamlining, standardizing, and error-proofing data, data files, tables, data sharing, and reports. 
  • Strong instincts for reviewing outputs and for discovering, correcting, and preventing data errors.

Desired Qualifications*

  • 3-5 years relevant work experience
  • Experience working with learning analytics datasets
  • Experience with SQL and constructing SQL queries
  • Experience with statistical, linguistic, and structural techniques to extract and classify information from textual sources
  • Familiarity with Peoplesoft and UM’s Data Warehouse
  • Experience with Tableau and/or Matplotlib

Additional Information

Excellent benefits are available, for details, see

NOTE: This is a five-year, term-limited position.

Background Screening

The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks.  Background checks are performed in compliance with the Fair Credit Reporting Act.

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.

Decision Making Process

Applications will be reviewed as received throughout the posting period and continue until the position is filled.

U-M EEO/AA Statement

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