Assistant Teaching Professor - Business Analytics
Listed on 2026-07-03
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Education / Teaching
University Professor
Position Title:
Assistant Teaching Professor - Business Analytics
Job Category:Academic Staff
Employment Type:Regular
Job Profile:Teaching Assistant Professor
Job Duties:The Austin
E. Cofrin School of Business at the University of Wisconsin–Green Bay seeks applicants for an Assistant Teaching Professor in Business Analytics. The Cofrin School of Business values university-level teaching experience, the ability to teach a variety of classes related to the candidate’s academic field and preparation, engagement in institutional, community, and professional service, and experience working in the world of business.
Consistent with UW–Green Bay’s mission, the successful candidate will contribute to a problem-focused educational experience that promotes critical thinking, student access and success, experiential learning, and strong connections to the regional business community, while working inclusively and effectively with a diverse campus community. Candidates with any research or teaching experience in the fields of artificial intelligence will be given strong consideration.
The successful applicant will contribute to a young, growing, forward-looking college and department embedded within Wisconsin’s third-largest metropolitan area. The Green Bay community is an affordable and growing city supporting significant collaborative opportunities with the business community. Northeastern Wisconsin’s proximity to the Great Lakes, a National Football League team, and the University’s Division 1 athletic program provides a foundation for a rich, high quality of life for its residents.
The Cofrin School of Business and the University of Wisconsin–Green Bay continue a sustained record (10+ years) of growth.
Job Responsibilities:
- Teach a normal instructional load of undergraduate and graduate courses in Business Analytics, Business Statistics, Decision Sciences (e.g., Management Information Systems, IT management, programming courses for business applications—especially R, Tableau, and MySQL, etc.), and/or Data Science. Candidates must be capable of teaching the above-mentioned courses from a business application perspective with examples relevant to the business world. Courses will be taught both in-person and online and may be taught in any of four other instructional modes (e.g., blended, interactive video).
- Mentor students to increase professional development, career advancement, and engagement in experiential learning opportunities inside and outside the classroom.
- Perform scholarly activities, service, and professional engagement activities consistent with the Cofrin School of Business expectations for an Assistant Teaching Professor.
- Perform institutional and community service.
- Contribute to ongoing development of the Cofrin School of Business and participate in AACSB accreditation efforts.
August 24, 2026
Department:Austin
E. Cofrin School of Business
Competitive salary commensurate with qualifications and experience.
This position is exempt from the overtime provisions of the Fair Labor Standards Act (FLSA).
Required Qualifications:- MBA or similar business Master’s degree, Master’s degree in Data Science, Management Information Systems, Data Analytics, Decision Sciences, IT (with a focus on business applications of IT), or related analytical field from an AACSB accredited institution
- Demonstrated potential for excellence in teaching
- Knowledge of programming and software like Python and R, along with knowledge of visualization software (e.g., Tableau).
The home campus of this position is Green Bay. Position is a full-time, 9-month, non-tenure track, Instructional Academic Staff appointment. Finalist(s) will need to consent to a verification of academic credentials through a third-party education check provider authorized by the University. A criminal conviction investigation will be conducted on the finalist(s). In compliance with the Wisconsin Fair Employment Act, the university does not discriminate on the basis of arrest or conviction record.
BenefitDetails
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