Description
The Division of Data Science and Society (DSS) at UNC-Chapel Hill’s School of Data and Information Sciences (SDIS) is excited to announce a full-time Professor of the Practice position in data science. This position provides academic leadership for the culminating capstone experience in the school’s graduate data science programs – the online Master of Applied Data Science (MADS) and the residential Master of Science in Data Science (MS) – and serves as the faculty lead for MADS. The successful candidate will orchestrate the delivery of the graduate capstone course, serve as instructor of record for the MADS capstone, and teach additional DATA courses in the MADS program as program needs require. Primary responsibilities include:
- Orchestrate the delivery of the graduate capstone course by vetting projects in conjunction with the school’s Office of Cross-Sector Partnership, overseeing and grading student work, and communicating with the external clients of capstone projects.
- Teach a wide range of the DATA courses offered in the MADS program, including the culminating capstone experience, in coordination with other teaching faculty.
- Serve on the Admissions Committee for MADS, reviewing candidates who meet program qualifications and making admission decisions.
- Collaborate with school staff on curricular improvements to ensure the online program management vendor delivers services that meet university academic standards.
- Oversee continuous quality improvement of the curriculum by reviewing instructor and student feedback and implementing changes.
- Take an active role in planning and carrying out the optional on-campus immersion held during the summer.
- Participate in virtual student recruitment sessions four times a year.
Professors of the practice at SDIS bring deep professional and pedagogical expertise into the classroom and play a central role in connecting students with real-world practice. Working closely with teaching faculty, program staff, the Office of Cross-Sector Partnership, and the school’s external partners, the Professor of the Practice will ensure that data science master’s students complete a rigorous, client-facing capstone experience that translates classroom learning into professional practice. We invite you to join the DSS faculty and be part of this mission.
The applicants must have a Ph.D. in data science, statistics, computer science, or a related field, or a master’s degree in a related field accompanied by substantial professional experience in the practice of data science.
Preferred applicants will have a strong record of teaching and mentoring at the graduate level, evidence of excellence in developing and delivering data science courses, and an aptitude for working collaboratively across disciplines. Teaching experience in formal online settings is a plus. Experience managing client-facing, project based courses, and communicating with external partners is preferred. Additionally, candidates must be able to engage with students, researchers, professionals, and stakeholders from diverse disciplines. A record of professional practice in data science is strongly preferred.
Visit https://unc.peopleadmin.com/postings/325070 to apply. All faculty candidates must apply online and submit a cover letter and resume. The “other document” in the list of required documents to be submitted is a teaching statement. Please arrange for four reference letter writers to submit letters where indicated. They will receive an email with instructions for submitting letters of recommendation. Please ensure that at least one of the four letters address your teaching experience and qualifications.
For full consideration, applications should be received by Monday, October 12, 2026. Anticipated starting date is January 1, 2027.
For inquiries, please contact us at dss-pop-2026@office.unc.edu.
The University of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, race, national origin, religion, sex, sexual orientation, or status as a protected veteran.
