Sessional - Faculty - DASC 6210

DUTIES

The Department of Data Science requires a sessional instructor to teach DASC 6210 – Data Analysis in Business and Economics during the Winter 2027 semester.

Duties include delivering lectures, seminars, and applied laboratory sessions, as well as marking assignments, case studies, tests, and examinations. The course is already developed and has been offered on a regular basis.

The successful candidate will be responsible for facilitating student learning in the application of data science, analytics, decision modeling, and optimization techniques in business and economic contexts. Course topics include decision analysis, risk analysis, spreadsheet modeling, business analytics, forecasting, regression modeling, optimization, simulation, multi-criteria decision making, dashboard development, and data-driven decision support systems. Students learn to integrate analytical methods and statistical models with managerial judgment to solve realistic business problems and support strategic decision-making.

The successful candidate should demonstrate the ability to teach graduate-level students and support experiential learning through case studies, business applications, analytical modeling, and practical data analysis exercises. Experience teaching business analytics, decision sciences, operations research, forecasting, applied statistics, or related fields will be considered an asset.

Other courses may be assigned depending on departmental needs and the qualifications and expertise of the candidate.

Thompson Rivers University (TRU), , is a uniquely comprehensive and student-focused institution built on over 50 years of excellence in post-secondary education and training. Located in Kamloops, British Columbia, TRU offers a dynamic learning and research environment that combines academic excellence, innovation, and strong community connections. Kamloops provides outstanding recreational, cultural, social, and economic opportunities and enjoys more than 2,000 hours of sunshine annually.

QUALIFICATIONS

Required Qualifications

1. PhD's degree in Data Science, Business Analytics, Statistics, Economics, Operations Research, Industrial Engineering, Management Science, Computer Science, Mathematics, or a closely related discipline.
2. Demonstrated expertise in data analysis, statistical modeling, decision analysis, business analytics, optimization, forecasting, and quantitative decision-making.
3. Experience using analytical software and tools such as R, Python, Tableau, Power BI, or equivalent platforms.
4. Ability to effectively teach graduate-level students.
5. Strong communication skills and fluency in spoken and written English.

Preferred Qualifications

1. Prior university-level teaching experience.
2. Experience teaching business analytics, data analytics, management science, decision analysis, optimization, forecasting, applied statistics, or related courses.
3. Evidence of teaching effectiveness through teaching evaluations, curriculum development, instructional innovation, or a teaching dossier.
4. Experience applying analytical and predictive modeling techniques to real-world business, economic, or industry problems.
5. Experience supervising graduate students and facilitating case-based or project-based learning.
6. Professional experience in business analytics, decision support systems, management consulting, data science, or a related industry setting.