MADS Section Instructor

A global higher education leader in innovative teaching, research and public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation's top public universities. Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn.

One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural, recreation and professional opportunities that span the campus and community.

University employees can choose from a wide range of professional training opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks that include numerous retail and restaurant discounts, savings on local child care centers and special rates for performing arts events.

In 2022, UNC Chapel Hill launched the School of Data Science and Society ( SDSS), a new school devoted to data science teaching, research, scholarship, service, and creativity. The SDSS vision is to be a leader in shaping the field of data science through an interdisciplinary and rigorous grounding in theory and methods with a human centric approach to the entire data life cycle.

The mission of SDSS is to empower a diverse community of faculty conducting research in the fundamentals and/or the applications of data science. The school is training undergraduate, graduate, and professional students to be the next generation of data science leaders with the knowledge and skills to thrive in this data-driven world. The SDSS will serve the state, the nation, and the world through premier data science educational programs and innovative research directed to advancing the public good with human-centric and ethical applications.

The core elements of the SDSS include porous borders - leveraging our low-walled collaborative Carolina culture to solve major societal problems. Interdisciplinary research clusters that cross disciplines and school boundaries are a vital element of the school. The SDSS is focused on students and education - the emphasis is not just on data science majors but on all students becoming data literate. The school's culture has an open and transparent structure, governance, and business model.

Part-time Section Instructors will teach an online class (or a combination of classes) for the School of Data Science and Society's new Master of Applied Data Science ( MADS) degree. Section Instructors are hired for a period of two years but may teach different courses over that period of time (and do not have to teach every semester). To see a list of potential course offerings, please go here - https://datascience.unc.edu/sectioninstructor/.

Section Instructors for the online Masters of Applied Data Science use their unique background and expertise to engage students as they work through 13 weeks of content that follows a standardized course syllabus, class plan, and pre-developed instructional materials created by Lead Faculty.

Section Instructors are expected to
Bring their unique background and expertise to the course experience.
- Help students apply course material and their newly acquired knowledge to relevant, real-world problems.
- Effectively engage class members in discussions.
- Support student learning by establishing and communicating regular office hours and responding to student issues and questions.
- Maintain reliable access to the learning management system (e.g., meeting technical specifications and reliable high-speed internet access).

Key responsibilities:
- Facilitate 13 weekly live online sessions class discussions that apply learning from self-paced modules developed by lead faculty. Synchronous class sessions will be scheduled for weekday evenings, and they must occur at the same day and time each week.
- Grade assessments and discussion and provide verbal and written feedback to students as appropriate.
- Respond to student questions and issues related to the course.
- Maintain regular communications with Lead Faculty and the MADS program leadership about students' experiences, potential barriers, ideas for enhancement, and any other topics relevant to the course or students.

Bachelor's degree required (or foreign degree equivalent); The qualifying degree should be in the same discipline, or one closely related to the subject matter of the course to be taught.

A minimum of 3 years of relevant work, research or teaching experience in the same discipline, or one closely related to the subject matter of the course to be taught.

An earned master's degree from an accredited institution, or the equivalent, is preferred.
An earned doctorate or terminal degree in the same or closely related discipline as the course to be taught is preferred.
Experience and/or expertise in an industry/government/NGO/community organization setting that relates to the subject matter of the course to be taught is strongly preferred.
Experience teaching in higher education, graduate-level data science courses, and/or online settings is preferred.

N/A

Not Applicable.

General information on the MADS program: https://online.unc.edu/online-masters-programs/masters-data-science/ . To see a list of potential course offerings, please go here - https://datascience.unc.edu/sectioninstructor/ .

All faculty candidates must submit a cover letter, resume, and a list of 1-3 references with their contact information so that they may be contacted to provide a recommendation letter.

If you experience any problems accessing the system or have questions about the application process, please contact the University's Academic Personnel Office at facultyrecruitment@unc.edu.

Please note: The Academic Personnel Office will not be able to provide specific updates regarding position or application status.

If you have any questions about the job requirements or the hiring department notify the Department Contact.

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, national origin, race, religion, sex, sexual orientation, or status as a protected veteran.