Professor of Analytics and AI

Recruitment Plan
I. RECRUITMENT PLAN
Posting Number:

F002669

Academic

Title:

Professor of Analytics and AIRank:

Assistant Professor Administrative

Title:

Discipline Business Specialty :

Contract Type:

Tenure Track Required Licenses/Certifications and other Specific Requirements:

Criminal History Screening, Education/Degree/Certifications Verification, Social Security Number Trace, and Sex Offender Registry Search, This position requires a licensure, certification, or special requirements

Proposed

Start Date:

08/01/2027

Full-Time/Part-Time:

Full-Time Position Description

Summary:

The Department of Decision Sciences at the George Washington University School of Business invites applications for a full-time, tenure-track Assistant Professor of Analytics and AI position as early as Fall 2027. Salary is competitive and commensurate with experience and an established research record.

We particularly welcome methodological research that develops algorithms and mathematical models in computational and statistical machine learning, optimization, and algorithmic decision-making. We value both methodological advances and rigorous applied research on AI that help organizations improve prediction, optimization, and decision-making under uncertainty.

Specific

Duties and Responsibilities:

The successful candidate will conduct research for publication in leading journals and conferences, teach undergraduate and graduate courses in analytics and AI, mentor graduate students, and participate in university and professional service. A strong commitment to teaching excellence and student learning is essential, along with the ability and flexibility to teach a range of courses as departmental and program needs evolve.

The appointment will support the department’s business analytics programs and the AI Analytics track of the school’s new MS in AI for Business.

Minimum Qualifications:

Applicants must hold, or expect to complete by the appointment date, a Ph.D. in statistics, machine learning, operations research, operations management, computer science, industrial engineering, or a closely related field. Applicants must demonstrate strong potential for research excellence and publication in premier scholarly journals in closely related disciplines. Applicants must also demonstrate teaching excellence at the undergraduate and graduate levels, a commitment to high-quality teaching and student learning, and evidence of teaching effectiveness or the potential to excel in the classroom.

Advertised Salary:$190,000 - $205,000

Other Benefits:

This position is eligible for full-time health benefits. For more information, please visit: (Use the "Apply for this Job" box below)..

Other Information:

Special Instructions to Applicants:

Applications must include an up-to-date curriculum vitae and cover letter; the names and contact information of three references who may be asked to provide letters of recommendation; a research statement describing the applicant’s research experience, current interests, and future research agenda; and a teaching statement describing the applicant’s teaching interests, aspirations, and any prior teaching experience.

Please submit an online application by November 9th. Applicants are encouraged to initiate submission of their application materials by October 25th to facilitate possible discussions with members of the search committee during the INFORMS Annual Meeting.

Only complete applications will be considered. If you have any questions regarding the position, please contact Zhengling Qi (qizhengling). Review of applications will begin November 9, 2026, and continue until the position is filled.

Department Link:

Posting Close Date:

Open Until Filled:

Yes Background Screening Successful Completion of a Background Screening will be required as a condition of hire.

EEO Statement:

The university is an Equal Employment Opportunity employer that does not unlawfully discriminate in any of its programs or activities on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, or on any other basis prohibited by applicable law.

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