Assistant Professor, Teaching Stream - Data Science

Assistant Professor, Teaching Stream - Data Science

Location:
Toronto, Ontario, Canada
Salary:
Competitive
Type:
Permanent
Main Industry:
Search Education & Training Jobs
Other Industries & Skills: 
Finance, Banking & Insurance
Advertiser:
University Of Toronto
Job ID:
132241822
Posted On: 
06 September 2025
Date Posted: 07/14/2025
Closing Date: 11/17/2025, 11:59PM ET
Req ID: 44011
Job Category: Faculty - Teaching Stream (continuing)
Faculty/Division: Faculty of Arts & Science
Department: Department of Statistical Sciences
Campus: St. George (Downtown Toronto)

Description:

The Department of Statistical Sciences in the Faculty of Arts and Science at the University of Toronto invites applications for a full-time teaching stream position in the area of Statistical Sciences. The appointment will be at the rank of Assistant Professor, Teaching Stream with an anticipated start date of July 1, 2026.

This search aligns with the University’s commitment to strategically and proactively promote diversity among our community members (

Statement on Equity, Diversity & Excellence). Recognizing that Black, Indigenous, and other Racialized communities have experienced inequities that have developed historically and are ongoing, we strongly welcome and encourage candidates from those communities .

The successful candidate must hold a PhD in Statistics, Computer Science, Data Science, or a closely related discipline by the time of appointment, or shortly thereafter with a demonstrated a strong record of excellence in teaching.

We are seeking candidates whose teaching interests will complement and enhance the department’s strengths in education.

Applicants must have teaching experience in statistics, biostatistics, or data science within a degree-granting program, at the undergraduate level for students specializing in statistics or related fields with strong mathematical and computational components. This includes experience in course design, lecture preparation and delivery, curriculum development, and the creation of online educational materials.

Candidates must show a strong commitment to pedagogical excellence and innovation, as evidenced by engagement in teaching-related activities and pedagogical inquiry. A demonstrated interest in advancing teaching practices and curriculum development is essential.

Applicants should have expertise in the application of statistical methods in data science, machine learning, or artificial intelligence. Experience must include the preparation and delivery of course content that incorporates real-world data and applied statistical methods. Furthermore, we prefer that candidates have experience in interdisciplinary collaboration as a statistician or data scientist on projects involving genuine applications of statistical or data science methods.

Preferred qualifications include a demonstrated interest in supervising undergraduate research projects, experience managing large enrolment courses and teaching assistants, and a collaborative approach to course coordination and teaching.

Evidence of excellence in teaching and commitment to pedagogical scholarship should be demonstrated through teaching accomplishments such as teaching awards, peer-reviewed presentations at major conferences, a comprehensive teaching dossier (as outlined in the application instructions below), and strong letters of reference from referees of high standing.

Salary will be commensurate with qualifications and experience.

All qualified candidates are invited online at Academic Jobs Online, 

academicjobsonline/ajo/jobs/30220
and must submit a cover letter; a current curriculum vitae; and a complete teaching dossier to include a teaching statement, sample syllabi and course materials, and teaching evaluations.

E
quity, diversity and inclusion are essential to academic excellence as articulated in University of Toronto’s Statement on Equity, Diversity and Excellence
. We seek candidates who share these values and who demonstrate throughout the application materials their commitment and efforts to advance equity, diversity, inclusion, and the promotion of a respectful and collegial learning and working environment.

Applicants must also arrange to have three letters of reference (dated, on letterhead and signed) uploaded through Academic Jobs Online directly by the writers by the closing date. At least one reference letter must primarily address the candidate's teaching.

All applicant materials, including recent signed reference letters, must be received by November 17, 2025.

For more information about the Department of Statistical Sciences, our website at statistics.utoronto.ca or contact Katrina Mintis at katrina.mintisutoronto.ca
.

 

CAUTION
:
This ad is “posted only” to the U of T faculty job board. Please see the information above for application instructions. Applications submitted via the U of T platform will NOT be considered for this position.

All qualified candidates are encouraged ; however, Canadians and permanent residents will be given priority.

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.

If you require any accommodations at any point during the application and hiring process, uoft.careersutoronto.ca.

 

Apply:

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