Date Posted: 08/15/2025
Req ID: 44848
Faculty/Division: Faculty of Arts & Science
Department: Office of Teaching and Learning
Campus: St. George (Downtown Toronto)
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.
Arts & Science offers many resources to support teaching and students' learning. We strive to encourage and enable exemplary and innovative teaching, enrich and support student academic transition, and build connections between academic and non-academic learning. We support instructors and academic units in translating their goals into effective practice, building teaching expertise and capacity, and designing pedagogical resources and approaches.
The Teaching & Learning team in the Faculty of Arts & Science supports instructors and academic units in translating their goals into effective practice, building teaching expertise and capacity, conducting research and designing pedagogical resources, initiatives and approaches. The Computation and Data Science Education (CDSE) initiative aims to catalyze and support the integration of computation and data science across disciplines by providing pedagogical and technological support to faculty, postdoctoral fellows, and graduate students. In addition to supporting individual teaching teams and curricular efforts, the initiative will also serve as an interdisciplinary hub to bring together educators engaged in computation and data science teaching to share their experiences, best practices, and technological approaches.
Your opportunity:
Residing in the Office of the Dean, Teaching & Learning team, the Faculty Liaison Coordinator, CDSE will work closely with academic administrators, faculty members, course instructors and students to integrate computation and data science across Arts & Science disciplines.
Working collaboratively with faculty members, course instructors and academic administrators, the incumbent is expected to develop and implement coherent and integrated instructional strategies that support learning objectives, incorporating current best practices in teaching.
Yourresponsibilities will include:
- Researching and recommending options for computational and data science professional development for graduate students and faculty
- Conducting detailed pedagogical analysis and consultation to inform program planning activities
- Evaluating learning outcomes for program development, to help the faculty achieve its data science goals
- Keeping well-informed on current technologies, best practices and industry standards, including the integration of AI tools
- Advising instructors on strategies for developing and delivering curriculum
- Analyzing needs and recommending appropriate technologies for teaching/learning goals
- Developing content for instructional workshops
- Developing and implementing community engagement strategies and plans for the Computation and Data Science Education community of practice
Essential Qualifications:
- Master's Degree with a curriculum focus in data science or related fields, or an equivalent combination of education and experience.
- Minimum five years of experience developing and delivering pedagogical programming for faculty and staff, and experience providing consultations to faculty/staff on teaching and learning-related topics with a focus on computation and data science education
- Experience with designing and delivering data science courses and professional development programs at a post-secondary institution (e.g., programming, data analysis, data visualization, machine learning, generative AI pedagogies and the cross-over between data science and GenAI )
- Extensive experience coordinating the projects and strategic initiatives with multiple contributors and stakeholders
- Experience providing advice on pedagogical strategies for developing and delivering curriculum
- Demonstrated experience in analyzing needs, evaluating and recommending appropriate technology for teaching and learning goals
- Experience working with a range of e-learning tools and learning management systems
- Extensive experience supporting video conferencing in a teaching context
- Excellent communication skills (oral and written); ability to effectively present information
- Excellent analytical and research skills
- Superior ability to collaborate effectively and to foster a collaborative environment within
- Excellent presentation and group facilitation skills
- Demonstrated knowledge of and familiarity with various educational technologies and pedagogical approaches
- Superior proficiency with Microsoft Office 365 Suite, including Excel, Forms, Stream, SharePoint, Canvas, and Teams
- Strong initiative; superior tact and judgment; ability to successfully meet deadlines
Assets (Nonessential):
- PhD degree in Data Science or related field is an asset.
- Experience with teaching and training at the post-secondarylevel
- Strong proficiency supporting the use of generative AI (e.g., ChatGPT, Microsoft Copilot) in a teaching and learning context a strong asset.
To be successful in this role you will be:
- Communicator
- Insightful
- Organized
- Proactive
- Problem solver
- Team player
Note: This is a 2-year term position, with an end date of September 2027
This role is currently eligible for a hybrid work arrangement, pursuant to University policies and guidelines, including but not limited to the University of Toronto’s Alternative Work Arrangements Guideline.
Closing Date: 09/05/2025, 11:59PM ET
Employee Group: USW
Appointment Type: Budget - Term
Schedule: Full-Time
Pay Scale Group & Hiring Zone: USW Pay Band 14 -- $91,677. with an annual step progression to a maximum of $117,242. Pay scale and job class assignment is subject to determination pursuant to the Job Evaluation/Pay Equity Maintenance Protocol.
Job Category: Research Administration & Teaching
