Assistant Professor of Business Information Systems

University of Arkansas•Little Rock, AR

21h

About The Position

The University of Arkansas at Little Rock is a metropolitan research university that provides an accessible, quality education through flexible learning and unparalleled internship opportunities. At UA Little Rock, we prepare our more than 8,900 students to be innovators and responsible leaders in their fields. Committed to its metropolitan research university mission, UA Little Rock is a driving force in Little Rock's thriving cultural community and a major component of the city and state's growing profile as a regional leader in research, technology transfer, economic development, and job creation. The Assistant Professor of Business Information Systems is a 9-month, full-time faculty position in the Department of Marketing, Management, and Technology in the School of Business. The Assistant Professor will have expertise in advanced analytics processes (e.g., SEMMA, 6 steps), a strong foundation in analytical techniques (e.g., association analysis, decision trees, text analytics), and proficiency with applied tools (e.g., Statistica, RapidMiner, KNIME, Tableau, Power BI, SQL, Python, etc.). In addition, experience with artificial intelligence and machine learning, including developing and applying models as well as understanding their benefits and limitations in industry, teaching, and research, would be strongly preferred. This role will be assigned to teach courses such as Data Analysis and Reporting, Information Technology for Decision Making, or related subjects, and to deliver courses in multiple modalities (face-to-face, hybrid, and online). This position is governed by state and federal laws, and agency/institution policy.

Requirements

Ph.D. or D.B.A. degree in Business Information Systems or a closely related field from an AACSB-accredited school.
Teaching experience
Professional work experience supporting teaching assignments
Record of research

Nice To Haves

Experience with analytics tools and platforms (e.g., KNIME, RapidMiner, Tableau, Power BI, SQL, R, Python) is preferred
AI/machine learning experience (e.g., developing, using, pros/cons, etc.) in industry, teaching, and research is preferred.

Responsibilities

Teach required courses per semester (fall and spring), of which 2 to 3 may be different courses. Classes take place in the mornings, at night (1 night/week), and/or online.
During summers (subject to funding, department need, and availability), all full-time faculty members, including Instructors, may teach an additional 2 courses for 15% of their 9-month salary, over a 5-week period of time
Serve on University, College, School, and Department committees
Engage with the regional business community
Publish scholarly research
Other duties as assigned.