How to Apply
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.
Please Note: This is a 5 year term limited position with the possibility of renewal depending on funding.
The Center for Academic Innovation at the University of Michigan is seeking a Data Scientist to lead analysis across the Center. The Data Scientist will be responsible for supporting the Center’s mission to foster a data-informed culture to shape innovation in higher education. The Center is responsible for a large portfolio of innovations in higher education and lifelong learning, resulting in a varied data portfolio including data depicting MOOC learner engagement, Online & Hybrid degree learner experience, and residential student engagement with our personalized learning technologies. This position will report to the Associate Director, Research & Development.
Who We Are
The Center for Academic Innovation is a strategic priority for the University of Michigan. Through curricular innovation, tools for learning, and educational data and research, the center aims to shape the future of learning and redefine the role of the public research university by extending academic excellence, expanding public purpose, and ending educational privilege.
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 scale
Diversity, Equity and Inclusion
Learning and working in environments designed for equity and inclusivity are necessary for the U-M community to make progress on solving the problems that matter most to society. In addition to collaborating with faculty and staff on projects that explicitly focus on DEI, the Center for Academic Innovation uses inclusive design processes in all of our work. All interested applicants, including those from groups historically underrepresented in higher education, are encouraged to apply.
For more information, please visit our website: Academic Innovation.
- Lead the collection, analysis, and interpretation of data from various sources to suggest conclusions and support decision-making in AI products
- Help project teams understand the opportunities to use data analysis to inform the design and development of digital applications and online learning experiences that facilitate engaged and personalized learning experiences and produce analyses to achieve identified needs
- Develop and implement machine learning algorithms for use in software applications
- Create user-friendly data visualizations that adeptly increase awareness of initiatives eff across the office
- Enhance internal research capabilities within CAI 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 CAI and various research partners and advisory boards.
- Provide support for end-users of software applications and learning experiences to explain data collection practices, data visualizations displayed, and outcomes achieved.
- A master'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.
- 3-5 years of relevant work experience
- Significant experience with using python to conduct statistical analyses
- Significant experience with various statistical analysis techniques, such as analyses of variance, factor analysis, reliability analyses, natural language processing, statistical process control, linear and hierarchical modeling, etc
- Experience explaining data visualizations and statistical descriptors to audiences who are both unfamiliar and extremely familiar with statistics and data science
- 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
- Experience managing day-to-day project decisions, including providing constructive criticism to peers and employees
- Demonstrated ability to be self-directed and work both independently and 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
- Strong attention to detail
- Experience with the U-M Data Warehouse
- Experience working with learning analytics datasets
- Familiarity with FERPA regulations
- Experience working in a multidisciplinary, research-oriented environment
- Experience with various statistical analysis techniques, such as analyses of variance, factor analysis, reliability analyses, natural language processing, statistical process control, linear and hierarchical modeling, etc
This is not a remote position and any adjustments to a standard in-person schedule will be discussed during the hiring process.
The salary for this position will be based upon the selected candidate’s education and experience.
Must have legal authorization to work in the United States.
Excellent benefits are available, for details, see http://benefits.umich.edu/
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 will be performed in compliance with the Fair Credit Reporting Act.
Job openings are posted for a minimum of seven calendar days. This job 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.
U-M COVID-19 Vaccination Policy
COVID-19 vaccinations are now required for all University of Michigan students, faculty and staff across all three campuses, including Michigan Medicine. This includes those working or learning remotely. More information on this policy is available on the Campus Blueprint website or the U-M Dearborn and U-M Flint websites.