Teaching Faculty in Data Science

The College of Emerging and Collaborative Studies (CECS) at the University of Tennessee, Knoxville's (UTK) seeks a dynamic, collaborative, and innovative faculty memberto contribute to its existing and future programs in Data Science.

CECS 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 bythe 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 ascholarship focused on practice and impact; traditional academic research is welcome but not required.

Expertise in the following teaching areas is expected:

The College is especially interested in candidates whose primary strength lies in modern data engineering and MLOps, including ETL/ELT pipeline development, workfloworchestration, containerization, cloud-based data engineering,CI/CD, experiment tracking, model deployment, and monitoring andobservability 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 Git Hub, 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 skillsto 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.

• Teach courses spanning introductory through graduate level inData 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

• 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

• Significant professional experience in a relevant industry orapplied context (highly desirable)
• Relevant industry certifications, where applicable
• Record of applied scholarship: professional publications,conference presentations, tool or open-source…