Date Posted: 11/05/2026
Req ID: 50912
Faculty/Division: Faculty of Arts & Science
Department: Data Sciences Institute
Campus: St. George (Downtown Toronto)
Position Number: 00059926
Existing Vacancy: Yes
Description:
About us:
The Faculty of Arts & Science is the heart of Canada’s leading university and one of the most comprehensive and diverse academic divisions in the world. The strength of Arts & Science derives from our combined teaching and research excellence in the humanities, sciences and social sciences across 29 departments, seven colleges and 46 interdisciplinary centres, institutes and programs.
We can only realize our mission with the dedication and excellence of engaged staff and faculty. The diversity of opportunities and perspectives within the Faculty reflect the local and global landscape and the need for curiosity, innovative thinking and collaboration. At Arts & Science, we take pride in our legacy of innovation and discovery that has changed the way we think about the world.
Your opportunity:
The Data Sciences Institute (DSI) is a highly specialized research initiative at the University that draws on world-class research expertise across multiple academic divisions, affiliated hospitals, regional, national, and international academic partners, and commercial organizations. The mission of the DSI is to provide the leadership and capacity to catalyze the transformative nature of data sciences across disciplines, in fair and ethical ways, leveraging and strengthening U of T’s preeminence in data sciences. DSI supports and promotes the flow of methodological advancements such as data management, computing, data integration, visualization methods and facilitates the training of new generations of interdisciplinary trainees and upskilling of professionals. DSI aims to unify and galvanize the core strengths of Toronto’s data science community building capacity for data and computational-based projects and training by being the focal point for the coordination of data science activities and partnerships to further elevate UofT’s global stature.
Under the general directionof the Executive Director, DSI, the Research Solutions & Technical Enablement Lead will develop technical application implementation plans and determine key performance indicators to measure success. They will be the technical lead of the DSI and build and strengthen relationships with external stakeholders and partners.
The Research Solutions and Technical Enablement Lead will lead the development and execution of DSI training programs. The training programs are delivered across numerous platforms, including microcredential programs and targeted hands-on workshops and provide skills and training to a diverse participant landscape.
Your responsibilities will include:
- Developing and overseeing research-enabling software, platforms, tools, and computational resources to support complex data-intensive projects.
- Designing, testing, and modifying programming code
- Assessing and determining feasibility of research operational requirements and translating them into technical solutions and workflows.
- Building and strengthening relationships with stakeholders and partners of strategic importance, serving as a trusted advisor on technical and research enablement projects.
- Leading technical workshops, training and professional development seminars
- Researching and drafting materials for training content
- Keeping well-informed on current technologies, best practices and industry standards
- Directing the activities of a group of staff-appointed employees all performing a similar function, fostering a collaborative, inclusive, and high-performing team environment.
Essential Qualifications:
- Bachelor's Degreein Computer Science or Computer Engineering with specialization in AI, Machine Learning or acceptable combination of equivalent experience. A Master's Degree would be considered an asset.
- Eight years or more experience with advanced computing applications and designing highly complex scientific software
- Experience working in a post-secondary or research institution; familiarity with research funding opportunities and the drafting of research grant proposals
- Experience researching and creating bespoke training programs and curriculum in Artificial Intelligence, Machine Learning, Data Science or other related technical fields
- Experience facilitating technical training sessions
- Experience designing, testing and modifying program code
- Experience managing IT projects (Developing charter, scope, resources and schedule for projects)
- Experience supervising staff
- Strong programming skills in R and Python
- Superior organizational and time management skills; ability to to manage competing priorities and projects
- Self-starter, with proven ability to stay up-to-date on current technologies, best practices and industry standards
- Excellent verbal and written communication skills with the ability to communicate highly technical terms and concepts to people of non-IT backgrounds
- Strong relationship building skills, ability to work with diverse stakeholders (academic institutions, industry, government partners)
To be successful in this role you will be:
- Communicator
- Entrepreneurial
- Meticulous
- Motivated self-learner
- Organized
- Problem solver
- Team player
Closing Date: 11/13/2026, 11:59PM ET
Employee Group: USW
Appointment Type: Budget - Continuing
Schedule: Full-Time
Pay Scale Group & Hiring Zone:
USW Pay Band 18 -- $121,209 with an annual step progression to a maximum of $155,005. Pay scale and job class assignment is subject to determination pursuant to the Job Evaluation/Pay Equity Maintenance Protocol.
Job Category: Information Technology (IT)
Divisional HR Office Email: adminhr.artsci@utoronto.ca
Lived Experience Statement
Candidates who are members of Indigenous, Black, racialized and 2SLGBTQ+ communities, persons with disabilities, and other equity deserving groups are encouraged to apply, and their lived experience shall be taken into consideration as applicable to the posted position.
Job descriptions are available upon request for internal applicants.
