Description
A term adjunct position is open at the Smith School of Business for an instructor to teach at our main campus in Kingston, in a lecture-style undergraduate course in the Commerce program. The position is to teach Intro to Data Management and Analytics for Business – COMM 392 in the winter term. There are two sections available to teach. Teaching one (1) of these sections of COMM 392 will entail teaching 3 hours per week, in two 1.5-hour sessions (24 classes in a term), from January to April 2027. The successful applicant will be required to teach 100% of one or more sections of COMM 392, with a maximum enrollment of 55 students.
Course Description
This course provides an introduction to data management and analytics for business. The course will present a systematic view of analytics with a key focus on using data for business intelligence and descriptive analytics as well as an overview of predictive analytics and how they are used by businesses for creating a competitive advantage.
The course emphasizes the managerial aspects of analytics along with applications and implementation challenges, rather than technical issues (e.g. coding).
The course will also focus on how to understand and manage data as an asset that is at the core of value creation in today's digital age, with emphasis on technical aspects such as data structure, data models, and data preparation and exploration, as well as management aspects such as data reliability and quality.
Students will learn and apply relevant business intelligence and analytics concepts for solving various types of business problems using real data and practical business cases.
After completing the course, students will be able to do the following:
1. Organize data for answering business questions through applications involving data modeling, extraction, querying, and transformation.
2. Describe issues that can arise with data and the resulting models and implement techniques to address them effectively.
3. Explain how organizations can use business intelligence and data analytics, AI, and machine learning for operational and strategic purposes.
4. Use technology tools to perform descriptive data analytics, including data preparation, modeling, and visualization.
5. Build, train, test, evaluate, and deploy a machine learning model using graphical interface tools, and choose between competing models.
6. Communicate analytics results to managers and to a general business audience.
The open sections for COMM 392 have been scheduled in the Winter term as follows:
Section 001 - Tue 10:00 AM to 11:30 AM / Thur 08:30 AM to 10:00 AM
Section 002 - Mon 10:00 AM to 11:30 AM / Wed 08:30 AM to 10:00 AM
(Please indicate which section(s) you are applying for in your application.)
Compensation
The salary for a term adjunct teaching one section of a course in our Commerce program is $13,856 (excluding vacation pay). This salary is pro-rated based on course credit.
Qualifications
Qualifications include a Master’s degree or PhD; several years of related experience; and experience teaching university courses.
Application Instructions
Deadline for applications: September 30, 2026
Applicants should submit:
- A cover letter that explains your interest and ability to successfully deliver this course. Please tailor your cover letter to show how your previous experience has prepared you to be potentially successful.
- Current CV
- 2 letters of recommendation*
- Teaching evaluations if available
*Please list the names and email addresses of your referees on your Interfolio Faculty Search application. Interfolio will send an automated email to your referees and provide them with a link that will allow them to upload their recommendation letters.
Equal Employment Opportunity Statement
Smith School of Business at Queen's University shall abide by the requirements of 41 CFR §§ 60-1.4(a), 60-300.5(a) and 60-741.5(a). These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, or national origin. Moreover, these regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, national origin, protected veteran status or disability.
