Job ID

79373

Job Title

SESSIONAL FACULTY- Operations Management, 3DA3, Predictive Analytics, Winter 2027

Regular/Temporary

Temporary

Location

Central Campus

Open Date

2026/10/23

Job Type

Limited Term (<12 months)

Close Date

2026/11/05

Employee Group

CUPE Sessional Faculty

Favorite Job

Department

Operations Management

Full/Part Time

Part-Time

Job Code

001095

Existing Vacancy

Yes - Newly Created Position

Contract Duration

3.1 Months

Target Number of Openings

1

Hours per Week

4

Posting Details

NOTICE OF POSTING For Sessional Faculty

(DeGroote School of Business)

The Department of Operations Management invites applications for the following teaching position to be offered in the 2027 Winter session.

Department Contact: Dr. Yun Zhou, Area Chair, Operations Management

Course Name(s)/Number(s): 3DA3, Predictive Analytics

Term: Winter 2027

Number of Section(s) Available: 2 (C01, C02)

Number of Units per Section: 3

Location (on/off campus): Main

Projected Enrollment: 50 students per section

Projected TA Support: 50 hours per section

Start Time and Duration: Various

Wage Rate: $9,750 per section

Required Qualifications

A graduate degree in Operations Management, Business Analytics, Data Science, Statistics, Computer Science, Management Science, or a closely related discipline.

Demonstrated knowledge of predictive analytics, including regression, classification, model evaluation, cross-validation, and machine learning methods.

Proficiency in Python for data analysis, including data manipulation, exploratory analysis, visualization, and predictive modeling.

Demonstrated knowledge of statistical inference and its application to predictive analytics.

Ability to interpret analytical results and translate them into meaningful business insights.

Demonstrated ability to communicate quantitative and technical concepts clearly to undergraduate business students.

Strong communication, organizational, and interpersonal skills.

Preferred Qualifications

A PhD or PhD candidacy in Operations Management, Business Analytics, Data Science, Statistics, Computer Science, Management Science, or a related discipline.

Previous university-level teaching experience in predictive analytics, machine learning, business analytics, data science, or a closely related course.





Experience teaching Python and Jupyter Notebooks in an applied analytics setting.

Experience with supervised learning methods, including linear regression, classification, and tree-based models, as well as model validation and evaluation techniques.

Familiarity with unsupervised learning and selected advanced learning methods.

Experience using real-world datasets and business applications to teach predictive analytics and generate managerial insights.

*Supplemented Fees- Article 15.02 The employee may be eligible to receive supplemented fees in accordance with Schedule B of the Collective Agreement. The actual rate of pay when in excess of the base rate of pay is deemed to include any supplemented fees owing, to the extent of the excess amount. If the actual rate of pay is less than the sum of the base rate of pay and the supplemented fees owing, then the employee shall receive the difference.

How To Apply

1. A cover letter stating your intent to apply for the position (including your address, phone number, and email address) and emphasizing your experience with the material to be taught.

2. A resume listing your academic qualifications and relevant employment experience.
3. Information necessary to determine your current and aggregate seniority (as defined by Article 20 of Unit 2 Collective Agreement). www.cupe3906.org/unit-2-seniority-information/

4. Names and contact information of two references. Applicants will not be required to submit reference letters as part of their application.

Job applicants requiring an accommodation to participate in the hiring process should contact the Human Resources Services Centre at (phone hidden) ext. 222-HR (22247) to communicate accommodation needs.

Employment Equity Statement

McMaster University is located on the traditional territories of the Haudenosaunee and Mississauga Nations and within the lands protected by the “Dish With One Spoon” wampum agreement.





The diversity of our workforce is at the core of our innovation and creativity and strengthens our research and teaching excellence. In keeping with its Statement on Building an Inclusive Community with a Shared Purpose, McMaster University strives to embody the values of respect, collaboration and diversity, and has a strong commitment to employment equity.

The University seeks qualified candidates who share our commitment to equity and inclusion, who will contribute to the diversification of ideas and perspectives, and especially welcomes applications from indigenous (First Nations, Métis or Inuit) peoples, members of racialized communities, persons with disabilities, women, and persons who identify as 2SLGBTQ+.

As part of McMaster’s commitment, all applicants are invited to complete a confidential Applicant Diversity Survey through the online application submission process. The Survey questionnaire requests voluntary self-identification in relation to equity-seeking groups that have historically faced and continue to face barriers in employment. Please refer to the Applicant Diversity Survey - Statement of Collection for additional information.

Job applicants requiring accommodation to participate in the hiring process should contact:

- Human Resources Service Centre at (phone hidden) ext. 222-HR (22247), or
- Faculty of Health Sciences HR Office at ext. 22207, or
- School of Graduate Studies at ext. 23679

to communicate accommodation needs.

Interview Experience

At McMaster University, we believe in a comprehensive and inclusive interview process. Our interview methods encompass a variety of approaches that allow our hiring teams to provide a versatile and accessible experience for engaging with our candidates. Throughout your recruitment process at McMaster, you may be requested to participate in a variety of formats, that may include in-person, virtual or recorded interviews.

If you have any questions as you move through the hiring process, please reach out to [email protected] or the HR contact associated with your position of interest.

AI Statement

McMaster and its third-party partners may use AI tools to screen, assess, or select applicants during the hiring process. Please note that currently our recruitment platform does not use AI nor is it part of our current recommended recruitment process.

📌 SESSIONAL FACULTY- Operations Management, 3Predictive Analytics, Winter 2027 (Canada)
🏢 McMaster University
📍 Canada