Title: Lecturer of Data Science

Employee Classification: Lecturer (Continuing)

Campus: University of North Texas

Division: UNT-Provost

SubDivision-Department: UNT-College of Information

Department: UNT-Information Science-133310

Job Location: Denton

Salary: Varies based on assignment

FTE: 1.00

Retirement Eligibility: ORP Eligible

About Us - Values Overview:

Department Summary

The Department of Information Science, one of three departments in the College of Information, promotes the understanding of, access to and use of data and information through teaching, research and service activities. The department prepares data and information professionals of the highest quality to serve in dynamic roles locally, nationally and globally. Faculty members of the department measure their success by the success of their students and the quality of intellectual contributions to the profession and society. The Department offers two bachelor’s degrees, four master's degrees, postmaster’s certificates, and a doctoral degree in Information Science. Detailed information about the department can be found at https://informationscience.unt.edu/.

UNT has a highly diverse campus with a wide range of languages spoken in addition to English. We welcome candidates who have experience with HSI/MSIs and/or who speak Spanish, Vietnamese, American Sign Language, Chinese (Cantonese, Mandarin and other variations), Arabic, Tagalog, Farsi, French, or/and Yoruba.

Position Overview

The Department of Information Science at the University of North Texas (UNT) invites applications for a Lecturer in Data Science position. Position will begin Fall 2025. We are seeking excellent candidates with interests in a wide range of topics within the mathematical, statistical, machine learning, artificial intelligence, data analytics, and foundations and applications of data science. We expect candidates to be able to successfully teach undergraduate and graduate Data Science courses as well as advise students in Data Science. The position carries a typical teaching load of four courses in each of the Fall and Spring semesters.

This is a nine month, full-time, non-tenure-track position. We seek candidates who will provide inspiration and leadership in teaching, who can leverage the strengths of the department’s dynamic faculty and programs, and who will build collaborative relationships in the University and profession.

Minimum Qualifications

Ph.D. or equivalent degree in Mathematics, Statistics, Data Science, Computer Science, Computer Engineering, Machine Learning, or a related discipline with published work or industry experience that utilizes extensive big data analytics and machine learning. Experience in using Python and alternative data analysis languages such as R is required.

Knowledge, Skills and Abilities

Ability to teach in-person and online courses.

Preferred Qualifications

Candidates will demonstrate evidence of effective teaching with experience/expertise in the broad areas of Data Science.

Required License/Registration/Certifications

Work Schedule:

varies based on assignment

Driving University Vehicle:

No

Security Sensitive:

This is a Security Sensitive Position.

Special Instructions:

Benefits:

For information regarding our Benefits, click here.

EEO Statement:

The University of North Texas System is firmly committed to equal opportunity and does not permit -- and takes actions to prevent -- discrimination, harassment (including sexual violence) and retaliation on the basis of race, color, religion, national origin, sex, sexual orientation, gender identity or expression, age, disability, genetic information, or veteran status in its application and admission processes, educational programs and activities, facilities and employment practices. The University of North Texas System immediately investigates complaints of discrimination and takes remedial action when appropriate. The University of North Texas System also takes actions to prevent retaliation against individuals who oppose any form of harassment or discriminatory practice, file a charge or report, or testify, assist or participate in an investigative proceeding or hearing.