Job Description

Date Posted: 07/21/2026
Req ID: 49473
Faculty/Division: Faculty of Arts & Science
Department: Dept of Economics
Campus: St. George (Downtown Toronto)
Existing Vacancy: Yes

Course Number and Title:

MMF2030H1F: Machine Learning (Section LEC 0101)

Course Description:
The course will cover machine learning from both a theoretical and practical point of view, with a focus on pragmatic applications & real industry examples. Topics will cover supervised & unsupervised learning, as well as high level workflows from business problem definition down to analysis and integration with business strategy. Students will be encouraged to understand problems from a quantitative point of view, as well as through the lens of strategy and business usage. The course will cover theory, applications & common usage of key machine learning techniques, as well as case studies from the financial and professional services industries. The course evaluation will be based on participation and a group project, where students will be encouraged to apply a range of techniques covered to a business problem.

Estimated course enrolment 30

Estimated TA support n/a

Class Schedule Class Schedule: Tuesday 6:00 -9:00pm

The delivery method for this course is in-person.

Sessional dates of appointment October 6 – November 3, 2026

Salary (per section):

$9,997.48 Sessional Lecturer I

$10,699.22 Sessional Lecturer I - Long Term

$10,699.22 Sessional Lecturer II

$10,953.96 Sessional Lecturer II - Long Term

$10,953.96 Sessional Lecturer III

$11,228.90 Sessional Lecturer III - Long Term

Please note that should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.

Minimum qualifications:

• Advanced degree in Mathematical Finance
• Industry experience in supervised and unsupervised learning modern applications of machine learning
• Prior experience teaching this course (or a similar course) at the university level
• Ability and experience teaching large classes
  
  

Preferred qualifications:

• Industry experience in integration with business strategy
  
  

of duties

• Preparation and delivery of lectures in this course
• Preparation, supervision and grading of tests and examinations in accordance with university regulations
• Providing scheduled office hours for academic counseling of students
  
  

Application instructions:

Applicants should submit an updated curriculum vitae; names and contact information (email and phone) for two referees or two reference letters; evidence of teaching in the relevant area, including student evaluations if available; and the CUPE 3902 Unit 3 application form located here: https://www.economics.utoronto.ca/index.php/index/recruiting/sessionalOpeningsForm

Please attach the additional documents in one PDF file format to the application form. If you have any questions, please contact sessional.economics@utoronto.ca All applicants must have a valid email address.

Closing Date: 08/14/2026, 11:59PM EDT
**

This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement.

It is understood that some announcements of vacancies are tentative, pending final course determinations and enrolment. Should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.

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 of the CUPE 3902 Unit 3 collective agreement.

Please note: Undergraduate or graduate students and postdoctoral fellows of the University of Toronto are covered by the CUPE 3902 Unit 1 collective agreement rather than the Unit 3 collective agreement, and should not apply for positions posted under the Unit 3 collective agreement.