Southern Utah University’s Department of Marketing, Entrepreneurship, Sales, and Analytics (MESA) in the Dixie L. Leavitt School of Business invites applications for a tenure-track Assistant Professor of Business Analytics. This is a full-time, nine- month faculty appointment beginning in August 2026.
We seek an innovative educator and scholar with a Ph.D. in Business Analytics, Data Analytics, or a closely related field. The ideal candidate will provide excellent teaching and student mentoring, maintain an active program of scholarly or professional engagement to meet AACSB academic qualification standards, and contribute to service at the department, school, and university levels.
This position offers a dynamic opportunity to shape a growing analytics program and inspire the next generation of business analytics professionals in a student-centered, collegial environment.
We are unable to sponsor or take over sponsorship of an employment visa at this time.
Teach and develop curriculum for undergraduate and graduate
courses in Business Analytics. Expected teaching load is 3-4
courses per semester (depending on research productivity).
Summer course(s) may be available to teach for additional
compensation.
Mentor and engage students through high-impact educational practices, such as internships, student clubs, and one-on-one advising, consistent with SUU’s personalized, “T-Bird”
learning experience.
Maintain an active research agenda in analytics to contribute to the discipline and meet AACSB Scholarly Academic
qualifications. The Leavitt School of Business values
scholarly output. A typical faculty member is expected to
produce research sufficient to remain academically qualified
per AACSB standards while enjoying a supportive
environment for cross-disciplinary collaboration. Please see
the Faculty Qualification Policy for more details.
Provide service and leadership to the department, school, and university. This includes serving on committees, assisting
with program accreditation and assessment, developing
industry partnerships for the analytics program, and
contributing to community and outreach initiatives. Faculty
are also expected to foster SUU’s culture of caring by
supporting student success initiatives and a positive campus
community.
Minimum Qualifications
An earned doctorate in Business Analytics, Data Analytics, or
a related field, along with significant business analytics
experience, is required.
ABD candidates with a planned completion date by August 15, 2026 are welcome to apply.
Applicants must meet the Leavitt School of Business faculty qualifications standards for the appropriate AACSB
classification.
Applicants must meet the academic requirements to qualify for the Scholarly Academic (SA) category or the academic and professional requirements to qualify for the Practice Academic (PA) category. Please seeBusiness Faculty/Staff Resources | SUU for additional information.
Applicants must have an active research agenda in areas
relevant to their teaching assignment.
Applicants must demonstrate an ability to provide an excellent educational experience for students.
Applicants must demonstrate excellent communication and
interpersonal skills, with a collaborative approach to working with colleagues and mentoring students. The department values faculty who contribute positively to our supportive, “students-first” culture.
Preferred Qualifications
Relevant teaching experience at the university level.
Experience engaging and mentoring students in co- and extracurricular activities, and in the exploration of career opportunities and job placement within the discipline.
Experience with online course development and teaching.
Relevant professional experience.
Demonstrated expertise in machine learning, artificial intelligence, and predictive analytics with applications in business contexts (e.g., marketing, operations, finance, healthcare, supply chain).
Proficiency with data science programming languages such as Python and R, including machine learning libraries/frameworks (e.g., scikit-learn, TensorFlow, PyTorch) 7. Strong understanding of statistical modeling, supervised/unsupervised learning, and deep learning techniques.
Knowledge of data management and visualization tools (e.g., SQL, Tableau, Power BI, matplotlib, seaborn).
Ability to integrate emerging technologies (e.g., generative AI, responsible/ethical AI, cloud-based analytics platforms) into curriculum and research.
Proficiency in database management and querying (e.g., SQL, relational and non-relational databases).
Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud) for data storage, processing, or deployment.
Upload a 3-5 minute video outlining you research theme and pipeline. This will be submitted via pdf with an accessible link.
Contact information for three references.
Teaching evaluations if available.
Position is contingent on funding.