Sessional Lecturer - MGOC15H3 F

Job Description

Overview

• Date Posted: 03/02/2026


• Req ID: 47151


• Faculty/Division: UofT Scarborough


• Department: UTSC:Dept-Management


• Campus: University of Toronto Scarborough (UTSC)

Course

• Course Code and Title: MGOC15H3: Introductory Business Data Analytics


• Number of Openings: est. 2


• Lecture Sections: TU & TH 7:00pm-9:00pm

Course Description

The course lays the foundation of business data analytics and its application to Management. Using state-of-the-art computational tools, students learn the fundamentals of processing, visualizing, and identifying patterns from data to draw actionable insights and improve decision making in business processes. Students will also apply their theoretical learning through a series of IBM-led business cases.

Qualifications

Required: PhD in a relevant field such as Operations Research, Management Science, Industrial Engineering, Computer Science, Data Science, Statistics, or a closely related discipline; or a Master’s or Bachelor’s degree in a related field with substantial and relevant industry experience in business analytics, data analytics, operations, or decision support. Demonstrated knowledge of data analytics methods appropriate for an introductory business analytics course, including data manipulation, descriptive analytics, basic statistical analysis, and data visualization. Experience using common analytics tools and programming environments such as Python, R, Excel, SQL, or comparable platforms used in applied business analytics. Ability to explain analytical concepts clearly to undergraduate students with diverse quantitative backgrounds. Must have access to IBM Labs in Canada, and access and experience in associated data software, for the purposes of teaching.

Preferred: Prior teaching experience at the undergraduate or graduate level, particularly in analytics, operations management, or related quantitative courses. Industry experience applying data analytics to real-world business or operational decision making. Familiarity with modern computational tools and pedagogical approaches for teaching data-driven decision making. Strong communication skills and experience working collaboratively in a multi-instructor teaching environment.

Duties

This is a course taught jointly by one faculty member and two instructors. Responsibilities include the design and teaching of a university credit course, preparation and delivery of course content; development, administration and marking of assignments, tests and exams; calculation and submission of grades; holding regular office hours and maintaining reasonable availability for student and administrative contact; supervision of TAs assigned to the course. Instructors must support travel to IBM Labs during regular course time. Approximately 50 minutes per student enrolled over 30.

Application Instructions

All applicants who wish to be considered for a particular position must submit an application form, updated curriculum vitae (including a valid email address) and applicable teaching evaluations (if available). Online: https://www.utsc.utoronto.ca/webapps/cupehiring/dept/mgtu/app/sl. E-mailed applications and applications through SuccessFactors will NOT BE ACCEPTED.

Application Deadline: March 20, 2026

Hiring Notes

Please refer to the official posting for the timetable. Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12. In considering qualified applicants, teaching excellence, currency in and mastery of subject area; previous experience in teaching a similar course at undergraduate level or similar environment; several years related professional experience shall be the criteria used in the selection of the most qualified candidate in accordance with Article 14:12.

Candidates who are members of Indigenous, Black, racialized, and 2SLGBTQ+ communities, persons with disabilities, and other equity-deserving groups are encouraged to apply, and their lived experience shall be taken into consideration as applicable to the posted position. The rates stated in the collective agreement prevail if they differ from those in this posting. Undergraduate or graduate students and postdoctoral fellows of the University of Toronto are covered by CUPE 3902 Unit 1 rather than Unit 3.

Schedule

Classes are in-person and run May 4, 2026 to June 16, 2026. Exams: June 17, 2026 to June 20, 2026. All positions involve completion of all course grading and must be available throughout the exam period.

Salary

Salary for a half-course (0.50 FCEs) inclusive of vacation pay: Sessional Lecturer I: $9,820.70; Sessional Lecturer I-Long Term: $10,510.04; Sessional Lecturer II: $10,510.04; Sessional Lecturer II-Long Term: $10,760.28; Sessional Lecturer III: $10,760.28; Sessional Lecturer III-Long Term: $11,030.36.

Closing Date: 03/20/2026, 11:59PM EDT

This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement. If rates stipulate in the collective agreement vary, the rates stated in the collective agreement prevail.

Diversity and Accessibility

The University of Toronto embraces diversity and is building a culture of belonging. We encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. A brief Diversity Survey may be completed as part of the application. The survey is voluntary and results are aggregated for institutional planning purposes. For more information, see the University of Toronto Diversity page. The University is committed to the Accessibility for Ontarians with Disabilities Act (AODA) and to providing accommodations as required. If you require any accommodations at any point during the application and hiring process, please contact uoft.careers@utoronto.ca.