Teaching Faculty in Data Science

Teaching Faculty in Data Science Location: UTK Knoxville, Tennessee Open Date: Sep 7, 2026 Description: The College of Emerging and Collaborative Studies at the University of Tennessee, Knoxville seeks a dynamic, collaborative, and innovative faculty member to contribute to its existing and future programs in Data Science. The College has one position open in Data Science for a non-tenure track, nine-month, full-time appointment, on campus, beginning January 1, 2027. This is an open-rank search; appointment at the Teaching Assistant Professor, Teaching Associate Professor, or Teaching Professor level will be commensurate with qualifications and experience. The selected candidate will be responsible for teaching and service, with assignments made by the dean according to enrollment demands and scheduling. Primary teaching responsibilities will include courses in Data Science spanning introductory through graduate-level offerings, as well as other new courses launched by the College. We are seeking a colleague who brings deep applied expertise in one or more data science domains and who shares our commitment to education that is hands‑on, intercollegiate, and workforce‑relevant. Candidates are expected to maintain a scholarship focused on practice and impact; traditional academic research is welcome but not required. Expertise in the following teaching areas is expected: Data Science: The College is especially interested in candidates whose primary strength lies in modern data engineering and MLOps, including ETL/ELT pipeline development, workflow orchestration, containerization, cloud‑based data engineering, CI/CD, experiment tracking, model deployment, and monitoring and observability for data and models, as this is a current strategic priority for the program. Beyond that focus, expertise is also expected in: foundational data science concepts including data collection, management, and exploration; data stewardship, ethics, and lifecycle management; data storage, warehousing, and governance; analytical methods including statistics, machine learning, and optimization; advanced data analysis including multivariate regression, clustering, topic modeling, and time series analysis; data wrangling and preprocessing; visual analytics; programming in Python and R; version control using Git, collaborative platforms such as GitHub, and reproducible computing environments such as Jupyter; database design and SQL; and communicating data science outcomes to technical and non‑technical audiences. The ideal candidate will bring the knowledge and skills to teach courses such as Applied Cloud Computing for Data Science, Fundamentals of Data Engineering, Scalable Data Mining and Analysis, Edge and IoT Data Science, and Spatial Data Science, should the program choose to offer them in the future. Key Responsibilities Teach courses spanning introductory through graduate level in Data Science, including lab-intensive and applied learning components Develop and regularly update course materials to reflect current tools, frameworks, and industry practice Collaborate with intercollegiate program faculty to design integrative learning experiences that connect technical skills with ethical, policy, and real‑world application context Advise and mentor students, including supervision of capstone projects and applied research Maintain an active applied scholarly or professional practice profile relevant to your specialization; traditional academic research is welcome but not required Contribute to program assessment, continuous improvement, and accreditation processes Participate in college governance, committees, and professional community engagement Qualifications Ph.D. in Data Science, Statistics, Applied Mathematics, Computer Science or a closely related quantitative field Demonstrated expertise in one or more of the data science teaching areas listed above Evidence of effective teaching at the university level, or substantial practitioner experience with instructional or mentoring responsibilities Experience or demonstrated ability in the design and delivery of courses in multiple formats, including face‑to‑face, synchronous online, asynchronous online, and hybrid modalities Experience with technology‑enhanced teaching and team‑based instructional practices Commitment to applied, hands‑on, and workforce‑oriented undergraduate education Preferred Qualifications Significant professional experience in a relevant industry or applied context (highly desirable) Relevant industry certifications, where applicable Record of applied scholarship: professional publications, conference presentations, tool or open‑source software development, or practice‑based projects Experience developing or delivering simulation‑based, lab‑intensive, or capstone learning experiences Demonstrated ability or interest in teaching across disciplinary boundaries (e.g., data science and applied AI, or data science and a domain application such as sport analytics or health data) Familiarity with curriculum development, program assessment, or accreditation processes (e.g., ABET, SACSCOC) Experience mentoring students from diverse backgrounds in technical fields Faculty Rank Criteria Appointment rank will be determined based on the following criteria: Teaching Assistant Professor – Holds a Ph.D. (or will hold at the time of appointment) in a related field with promise for excellence in teaching and related responsibilities, evidenced by early effectiveness and contributions. Teaching Associate Professor – Terminal degree with a demonstrated record of excellence in teaching and related responsibilities, with a minimum of three years of full‑time teaching experience in a related field. Teaching Professor (Full) – Terminal degree with a sustained, consistent record of excellence and evidence of instructional leadership (e.g., curriculum development, mentoring, pedagogical innovation) commensurate with senior rank. Note: Applicants must be authorized to work in the United States. The college is unable to provide visa sponsorship for this position. Questions about the position should be directed to CECS Senior Director of Academic Operations, Elis Vllasi, email: View email address on click.appcast.io . Positions to be filled as soon as possible. To apply go to About the College The College of Emerging and Collaborative Studies at the University of Tennessee, Knoxville is at the forefront of changing the future of higher education. It is a first‑of‑its‑kind college created to meet the needs of students seeking a customizable degree path in emerging fields such as artificial intelligence and data science that leads to rewarding careers upon graduation. CECS offers timely, innovative, student‑centric degrees, minors, and stackable certificates at both undergraduate and graduate level that address the future talent gap and exposes students to experts and disciplines from across campus through cross‑cutting curriculum. CECS utilizes strong industry partnerships to ensure students gain relevant skills and real‑world experience, offering for‑credit internships and multi‑disciplinary projects. CECS emphasizes the cohort experience where students learn and interact with fellow students from across campus and disciplines, giving them the opportunity to learn from one another and work together to solve real‑world problems. Equal Employment Opportunity Statement All qualified applicants will receive equal consideration for employment and admission without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity, age, physical or mental disability, genetic information, veteran status, and parental status, or any other characteristic protected by federal or state law. In accordance with the requirements of Title VI of the Civil Rights Act of 1964, Title IX of the Education Amendments of 1972, Section 504 of the Rehabilitation Act of 1973, and the Americans with Disabilities Act of 1990, the University of Tennessee affirmatively states that it does not discriminate on the basis of race, sex, or disability in its education programs and activities, and this policy extends to employment by the university. Requests for accommodation of a disability should be directed to the ADA Coordinator at Equal Opportunity and Accessibility, 1840 Melrose Avenue, Knoxville, TN 37996-3560, by email to View email address on click.appcast.io, or by phone at View phone number on click.appcast.io. Inquiries and charges of violation of Title VI (race, color, and national origin), Title IX (sex), Section 504 (disability), the ADA (disability), the Age Discrimination in Employment Act (age), sexual orientation, or veteran status should be directed to the Office of Investigation and Resolution, 216 Business Incubator Building, E J. Chapman Drive, Knoxville, TN 37996-3560, by email to View email address on click.appcast.io, or by phone at View phone number on click.appcast.io. #J-18808-Ljbffr The University of Tennessee, Knoxville