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Job ID: 201307

Assistant Teaching Professor OR Lecturer - Business Analytics
University of Kansas


Date Posted Dec. 9, 2022
Title Assistant Teaching Professor OR Lecturer - Business Analytics
University University of Kansas
Lawrence, KS, United States
Department Business
Application Deadline Open until filled
Position Start Date Available immediately
 
 
  • Assistant Professor
  • Business - General
 
 

Assistant Teaching Professor OR Lecturer – Business Analytics
Business

Position Overview

The School of Business at the University of Kansas is searching for either an Assistant Teaching Professor or a Lecturer in Business Analytics and Information Systems for the 2023-24 academic year. All interested candidates should demonstrate their industry and/or teaching expertise in the areas of statistics and application of data analytics and information systems to contemporary business problems. This is a full-time, non-tenure, academic-year teaching position beginning August 18, 2023.

In a continuing effort to enrich its academic environment and provide equal educational and employment opportunities, the university actively encourages applications from members of underrepresented groups in higher education.

The successful candidate must have appropriate authorization to work in the U.S. before employment begins. Any employment with the University of Kansas is contingent upon satisfactory completion of a background check.

Job Description

80% Teaching
Teach undergraduate or graduate level courses in various topics in statistics, information systems, and/or business analytics. Duties include but are not limited to course preparation, consultation, and assignment of course grades. Courses may be taught at the Lawrence, Edwards, or Leavenworth campus or online. The course load for this appointment is four courses each semester (fall and spring). Course load and teaching assignments will be determined by the area director to best meet the needs of the School of Business. All teaching professors should abide by area, school, and university policies and procedures.

10-20% Service
Participate as an active member of the area and engage in instruction-related activities beyond direct instruction. Examples include curriculum development committees, course improvement initiatives, and advising student organizations. All faculty members are expected to fulfill their share of service duties needed to facilitate the efficient operation of the school.

0-10% Scholarly and/or industry engagement
Engage with practitioners in the business community to better understand current and evolving business practice and disseminate this knowledge within or outside the school to improve instruction and student development. Dissemination may take many forms, including but not limited to presentations or workshops for colleagues, participation on curriculum committees, case study, and case competition development. If desired, scholarly engagement may also include academic or pedagogical research, publications in academic or practitioner journals or textbook development.

Required Qualifications

For appointment at the rank of Assistant Teaching Professor:
A Ph.D. or D.B.A in a discipline directly related to statistics, information systems, or business analytics (e.g., data science, data engineering, data management, predictive analytics, information science, information systems, applied statistics, computational science, or quantitative social science). Degree must be earned by August 18, 2023.
Demonstrated (or high potential for) teaching excellence in information systems and/or business analytics.
Demonstrated (or high potential for) scholarly or industry engagement.

For appointment at the rank of Lecturer:
Master’s degree in Statistics, Business Analytics, Information Systems, or a related field.
Demonstrated record of teaching in an academic setting or a record of mentorship, leadership, or training experience in a professional setting.

Preferred Qualifications

Experience teaching successfully at both graduate and undergraduate levels.
Experience and with effective curriculum development and online instruction.
Experience with connecting and engaging with the business community.

Contact Information to Applicants

Deb Dey, deb.dey@ku.edu

Additional Candidate Instruction

To be considered, candidates must submit an online application. A complete application will include a:
letter of application describing both academic and/or industry experience and accomplishments, (See additional details below.)
record of productivity in teaching, research, service, and/or industry experience as noted in CV,
teaching statement and supplemental materials, as appropriate (e.g., teaching portfolio, sample syllabi, teaching evaluations).
Candidate interests in the areas of statistics, business intelligence, data visualization/graphics, information systems, machine learning, computer simulation and modeling, IT security, Big Data, scripting languages or programming frameworks (e.g. SQL, Python, R, SAS), data management platforms (e.g., Oracle, MS SQLServer) and/or analytics tools (e.g., Spotfire, Tableau) should be outlined in the cover letter required as a part of the application package. Additional relevant interests such as engagement with the business community on digital innovation, data analysis, and providing insights and solutions in the application fields of security, health care, energy, fraud detection, finance, retailing, and/or insurance should also be outlined in application materials.

Letters of recommendation will be requested from selected applicants as the search process moves beyond the initial screening round.

In addition to the materials above, learning about each applicant’s contribution and engagement in areas of diversity is an important part of KU’s mission. As a result, applicants will be presented the following question at the time of application, "Describe your experiences working with people from diverse backgrounds, and explain how those experiences reflect your commitments to diversity, equity, and inclusion." The response must be within 4,000 characters or less.

Review of applications will begin January 10, 2023 and continue until a qualified pool of applicants is identified.


 
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Contact Information

 
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