Description
The College of Emerging and Collaborative Studies (CECS) at the University of Tennessee, Knoxville's (UTK) seeks a dynamic, collaborative, and innovative faculty member to 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 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
The College of Emerging and Collaborative Studies (CECS) at the University of Tennessee, Knoxville's (UTK) seeks a dynamic, collaborative, and innovative faculty member to 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 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