Job Description

Summary

Consulting for Statistics, Computing, and Analytics Research (CSCAR) is a service unit within the University of Michigan’s Office of Research that supports U-M researchers in their work involving data analysis. CSCAR consultants work directly with investigators, including faculty, students, and staff, who are engaged in all areas of research conducted at the University. CSCAR seeks a Data Science Consultant to serve as a member of its core staff. This individual will collaborate closely with U-M researchers on challenging and innovative research questions.

The ideal candidate will be an excellent communicator with advanced statistical training and computing expertise, holding a graduate degree in Statistics, Biostatistics, Data Science, or Applied Mathematics. CSCAR consultants frequently encounter analytic challenges that require non-standard methods or the development of new statistical methods. Thus, a solid grounding in advanced statistical theory and evidence of creative statistical insight are essential. The work may require innovative analysis and computation involving data that exhibit complex and unconventional structure. Thus a consultant should have facility with a variety of computational tools including fluent data programming skills and an understanding of numerical algorithms used in data modeling and analysis. CSCAR consultants must be capable of managing multiple projects and responsibilities simultaneously, and should be able to set and meet goals with minimal supervision.

Responsibilities*

Collaborate with University of Michigan researchers
Hold one-on-one consulting appointments with U-M researchers.
Serve as an instructor for workshops in a classroom setting, and develop workshop materials.
Respond to questions sent to CSCAR via email.
Conduct statistical analyses for CSCAR clients.
Mentor and supervise graduate students working at CSCAR.
Required Qualifications*

A graduate degree in Statistics, Biostatistics, Data Science, or Mathematics.
A solid foundation in the theory of statistical data analysis.
Teaching and consulting experience at the university level.
Excellent computing skills, including facility with two or more computing environments commonly used for data analysis (e.g. SAS, SPSS, R, Julia, Stata, Matlab), programming experience in one or more common programming languages (e.g. C or Python), and facility with advanced computing environments including clusters and distributed data and computing infrastructure.
Excellent interpersonal skills and the ability to communicate advanced technical concepts clearly and effectively.
Strong background and interest in research design, and an interest in the broader goals of research in diverse fields.
A positive attitude toward continuously learning new skills.
A positive attitude toward helping researchers meet their goals.
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.