Date Posted: 09/29/2026 Req ID: 50283 Faculty/Division: Faculty of Arts & Science Department: Ctr for Industrial Relations Campus: St. George Downtown Toronto Description: Number of Positions: One 1. This posting is for a single appointmnt to teach both sections of the following course. Course Number and Title: IRE2004HS – Data Analytics and Metrics for IR and HR Course Description: This course is designed for students who have already completed an introductory statistics course and are ready to apply foundational statistical concepts to practical problems in human resource management and industrial relations. Emphasizing application over theory, the course covers techniques such as descriptive analysis, hypothesis testing, ANOVA, and multivariate regression within the context of HR functions including employee selection, compensation, and labor relations. Students will use R software to analyze HR data, assess policy effectiveness, and develop data-informed recommendations. The course highlights the importance of selecting appropriate analytical methods and recognizing common pitfalls in statistical reasoning. Estimated Course Enrolment: Two sections of approximately 40 students each. The successful candidate will be responsible for teaching both sections. Estimated TA Support: approx. total 120 TA hrs for both sections. Schedule: Tuesdays, 15:00 – 17:00 section 1 and Tuesdays, 18:00-20:00 section 2. Sessional Dates of Appointment: January 1 – April 30, 2027 Salary: Salary inclusive of vacation pay:Sessional Lecturer I = $19,994.95Sessional Lecturer I - Long Term = $21,398.43Sessional Lecturer II = $21,398.43Sessional Lecturer II - Long Term = $21,907.92Sessional Lecturer III = $21,907.92Sessional Lecturer III - Long Term = $22,457.80 Please note that should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement should prevail. Minimum Qualifications: Completed PhD in Industrial Relations, Human Resources, or a related discipline; or a combination of advanced degrees e.g., MIRHR, MBA, LLB in an applicable area and equivalent professional experience. Expert knowledge of the subject area is required. Familiarity with the use of R software for statistical analysis is also essential. Preferred Qualifications:Expert knowledge of subject area and demonstrated ability in university teaching. Previous experience in teaching a similar course is preferred. Description of Duties: Prepare a course syllabus in accordance with departmental guidelines. Prepare and deliver lectures 12 two-hour classes per section; be available for office hours and informal communications with students. Assess and evaluate students' work and provide final course grades in accordance with University and Department practices. Closing Date: October 21, 2026 Application Instructions: Applicants must submit an updated curriculum vitae, evidence of teaching in the relevant area including student
