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Lecturer In Statistics information

What are the key skills and qualifications needed to thrive as a Lecturer in Statistics, and why are they important?

To thrive as a Lecturer in Statistics, you need an advanced degree in statistics or a related field, strong analytical skills, and a solid grounding in statistical theory and methods. Familiarity with statistical software such as R, SAS, or SPSS, as well as experience with learning management systems, is typically required. Excellent communication, presentation, and mentoring skills help engage students and facilitate effective learning. These competencies are crucial for delivering high-quality education, supporting student success, and advancing research within the academic environment.

What are some typical challenges faced by a Lecturer in Statistics when balancing teaching and research responsibilities?

Lecturers in Statistics often juggle the demands of preparing and delivering high-quality lectures with maintaining an active research profile. Managing large class sizes, keeping course content up-to-date with evolving statistical methods, and providing individualized student support can be time-consuming. At the same time, there may be expectations to publish research and contribute to departmental projects, requiring strong time management and prioritization skills. Collaborating with colleagues, seeking research partnerships, and utilizing university support services are common strategies to successfully balance these responsibilities.

What is the difference between Lecturer In Statistics vs Teaching Assistant In Statistics?

AspectLecturer In StatisticsTeaching Assistant In Statistics
Required CredentialsMaster's or PhD in Statistics or related fieldEnrolled in or recent graduate of relevant program
Work EnvironmentUniversity classrooms, lecture halls, research settingsAssisting in courses, grading, tutoring
Employer & Industry UsageHigher education institutions, universitiesUniversities, colleges, academic departments
Common Search & Comparison IntentUnderstanding academic roles, career pathAssisting in courses, entry-level academic support

In summary, a Lecturer In Statistics typically holds advanced degrees and delivers lectures at universities, focusing on teaching and research. A Teaching Assistant In Statistics usually supports faculty by grading, tutoring, and assisting in classes, often being a graduate student. Both roles are integral to academic institutions but differ in responsibilities and qualifications.

What does a Lecturer in Statistics do?

A Lecturer in Statistics is an academic professional who teaches undergraduate and/or postgraduate courses in statistics at a college or university. Their responsibilities include preparing and delivering lectures, developing course materials, assessing student performance, and providing academic guidance. Additionally, they may conduct research in statistical theory or applied statistics and contribute to departmental administration. Lecturers often stay updated with advances in the field and may participate in academic conferences or publish scholarly papers.
What are popular job titles related to Lecturer In Statistics jobs in Ontario? For Lecturer In Statistics jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Lecturer In Statistics jobs in Ontario look for? The top searched job categories for Lecturer In Statistics jobs in Ontario are:
Lecturer In Statistics jobs near you
Infographic showing various Lecturer In Statistics job openings in Ontario as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 20% Part Time, and 4% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution.

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

University of Toronto

Toronto, ON • On-site

CA$4.9K/wk

Other

Posted 13 days ago

Job description

Date Posted: 07/21/2026
Req ID: 49466
Faculty/Division: Faculty of Arts & Science
Department: Dept of Economics
Campus: St. George (Downtown Toronto)
Existing Vacancy: Yes

Description:

Course Number and Title: 

MMF1922H1F: Data Science (Section LEC 0101)

Course Description:
Over the past decade, data science and machine learning have gained immense popularity in many scientific disciplines. The reason for the emergence is due to theoretical advances in machine learning, availability of big data, and surges in computational capabilities. This 8-week course provides an introductory overview of data science methods in finance, investments, and risk management. The course covers a review of foundational probability and statistics, brief introduction to machine learning (supervised learning, unsupervised learning) and big data tools.

Estimated course enrolment: 30

Estimated TA support: n/a

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

The delivery method for this course is in-person.

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

Salary (per section):

$4,998.74 Sessional Lecturer I

$5,349.61 Sessional Lecturer I - Long Term

$5,349.61 Sessional Lecturer II

$5,476.98 Sessional Lecturer II - Long Term

$5,476.98 Sessional Lecturer III

$5,614.45 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 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

Preferred qualifications:

  • Industry experience in big data and machine learning in finance

Description 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.

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