Data Science Fellow

The Center for Academic Innovation (AI) is hiring a data science fellow. AI is charged with creating a culture of innovation in learning. As a catalyst for innovation, we aim to shape the future of learning by unlocking new opportunities for enabling personalized, engaged, and lifelong learning for the U-M community and learners around the world (read more about AI).  

 

Since its inception, over 50,000 students have interacted with an AI-supported tool in some way. Additionally, there have been over 15 million enrollments in our online learning experiences. We’re looking for a student who is independent, detail-oriented, and reliable to help us analyze and draw inferences from user behavior to complement our research capabilities and ultimately improve the learning experiences we produce. 

Responsibilities

  • Take on research projects in the field of learning analytics
  • Develop measures to predict performance
  • Build creative data visualizations
  • Present findings and conclusions back to team members  
  • Implement algorithms into AI tools 

Required Qualifications

  • Currently pursuing a bachelor’s degree, master’s degree, or PhD in data science, quantitative psychology, education statistics, informatics, econometrics, or a related field.
  • Significant data analytics experience with an open-source or statistical programming language (R, Python, SAS, SPSS, etc.). 
  • Experience merging and cleaning large, dense datasets in CSV format.
  • Knowledge of, and experience with, advanced statistical analysis techniques, such as multilevel modeling, random effects, item response theory, cluster and factor analysis, etc. 
  • Demonstrated ability to be self-directed and work independently or as part of a rapidly changing, multidisciplinary, multicultural, and collaborative environment.

Desired Qualifications

  • Experience with adaptive testing algorithms and crossed (subject x item) random effects
  • Experience with using Problem Roulette

Hours 

10 to 15 hours per week 

Start Date: September, 2022 (flexible)

End Date: December 2022 (flexible) 

Contact 

Send a cover letter and resume to marmills@umich.edu. (Please add “Data Science Fellow” to your subject line.)

screencap of Sean Swider using ViewPoint tool