Assistant Professor of Information Systems & Business Analytics (AI)

About Hofstra
At Hofstra University, intellectual curiosity is not just aspirational – it is central to how we engage on a daily basis. Hofstra faculty work within a diverse scholarly community committed to student success, intellectual discovery, free inquiry, inclusivity, and collaboration.

Enrolling more than 10,000 students, Hofstra offers students an array of undergraduate and graduate academic programs spanning the arts, humanities, sciences, business, engineering, law, health care, communications, and more.

Our accomplished faculty collaborate with students to explore interdisciplinary questions and produce innovative research that lays the foundation for future personal and professional success. With a beautiful campus in Hempstead, NY, Hofstra’s location seamlessly merges the tranquility of coastal suburban living with the boundless opportunities of nearby New York City.

Hofstra University is dedicated to recruiting and retaining a highly qualified and diverse academic community of students, faculty, staff, and administrators respectful of the contributions and dignity of each of its members. We welcome applications from individuals of all backgrounds and experiences and are committed to building a diverse and inclusive community.

Description
The Frank G. Zarb School of Business at Hofstra University invites applications for a tenure-track Assistant Professor of Information Systems & Business Analytics with an emphasis on Artificial Intelligence, beginning Fall 2027. We seek a candidate specializing in artificial intelligence in business and organizations. Areas of particular interest include enterprise and agentic AI, human–AI collaboration, and responsible AI.

The Zarb School of Business is recognized for its high-quality undergraduate and graduate programs, including a nationally ranked Online MBA program and an Executive MBA program. The Department of Information Systems and Business Analytics offers BBA/MBA/MS programs in Information Systems, Business Analytics, Cybersecurity Management, and Business Operations & Healthcare Analytics. A proposed Doctor of Business Administration in Cybersecurity Management program is under review. For information about our programs and resources, our faculty, and our students, applicants are encouraged to visit the department website: https://www.hofstra.edu/info-systems-business-analytics/

Responsibilities include, but are not limited to:

• Teach undergraduate and graduate courses in information systems and business analytics, including business statistics and AI-related courses and contribute to curriculum development. Teaching assignments will reflect the candidate’s expertise and departmental needs.

• Publish scholarly research in high-quality academic journals.

• Contribute to departmental, school, and university service, including committee work and student engagement activities.

Qualifications
• An earned doctorate in information systems, business analytics, decision sciences, or a closely related discipline from a university with an AACSB-accredited business school or equivalent accreditation. ABD candidates will be considered, provided the doctorate is expected to be completed by the start of the appointment.

• Strong evidence of potential for publication in high-quality peer-reviewed journals and a coherent research agenda relevant to artificial intelligence in business and organizations

• Evidence of high-quality teaching or strong potential for teaching excellence with excellent communication skills, including the ability to teach business statistics at the undergraduate and graduate levels

• Strong desire to work in a collaborative environment, support our students through the mentoring process, and serve the Hofstra community.

Preferred Quals Summary
• The ability to contribute to core information systems teaching, such as systems analysis and design or database management, is preferred. Applied analytics and machine-learning expertise relevant to the candidate’s research and teaching, including experience with computational tools such as Python or R, is desirable. Interest in interdisciplinary collaboration and experiential learning is also preferred.