Sessional Lecturer - MMF1922H1F: Data Science (Section LEC 0101)

Description

The course provides an introductory overview of data science methods in finance, investments, and risk management. It covers a review of foundational probability and statistics, brief introduction to machine learning (supervised learning, unsupervised learning), and big data tools.

Sessional Dates

Sessional dates of appointment: September 10 - October 29, 2026

Salary

Sessions: $4,998.74 (Sessional Lecturer I), $5,349.61 (Sessional Lecturer I - Long Term), $5,476.98 (Sessional Lecturer II), $5,476.98 (Sessional Lecturer II - Long Term), $5,614.45 (Sessional Lecturer III), $5,614.45 (Sessional Lecturer III - Long Term)

Course Details

Course Number and Title: MMF1922H1F: Data Science (Section LEC 0101)

Class Schedule

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

Delivery Method

The delivery method for this course is in-person.

Qualifications

• Advanced degree in Mathematical Finance
• Industry experience in data science and machine learning methods in finance
• Prior experience teaching this course (or a similar course) at the university level
• Ability and experience teaching large classes

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.

Diversity Statement

The University of Toronto embraces Diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.

Accessibility Statement

The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission. The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.