Data Analyst, Teaching & Learning

Description:

About us:

The Office of the Vice-Provost, Teaching & Learning (OVPTL) (formerly known as Office of the Vice-Provost: Innovation in Undergraduate Education) supports ongoing and new efforts to enhance the quality and expand the reach of high-impact teaching and learning practices at the University of Toronto.

To support teaching and learning across the University, the OVPTL maintains a robust profile related to five key priorities:

1. Teaching Awards & Grants: Recognizing and funding staff and faculty who demonstrate commitment to innovation and excellence in teaching practices.

2. Curriculum Development: Working with institutional and divisional stakeholders to develop and assess course and program-level outcomes.

3. Teaching Initiatives: Stewarding the development of institutional frameworks and resources for innovative teaching practices, such as experiential learning, undergraduate research and generative artificial intelligence in teaching and learning.

4. Digital Transformation: Building and supporting systems that enable faculty, staff and students to achieve their academic goals.

5. Analytics: Leveraging data to enhance program planning, decision-making and student success.

Your opportunity:

Reporting to the Manager, Student Success Analytics, the Data Analyst, Teaching & Learning, will be part of a dynamic, collaborative, and innovative group focused on enhancing undergraduate student academic success at the University. By utilizing existing data tools and creating customized analyses and visualizations, you will identify areas of opportunity to support student retention, progression, and graduation for undergraduate students at the University of Toronto.

Current priorities include establishing and supporting a sustainable institutional reporting and analytics framework, enabling the University to use student engagement data for institutional planning, student success initiatives, and unit-level decision-making. This work will create institutional reporting capabilities that deliver consistent, aggregated reporting on student engagement by division; strengthen existing student success analytics by integrating engagement indicators with retention, progression, and graduation data; and develop a standard assessment and planning package using a common baseline set of reports.

The role will also contribute to other institutional projects that support the teaching and learning environment, potentially including the University’s Learning Analytics efforts using data from the learning management system (Canvas, known as Quercus at U of T), and other projects that provide key data insights to instructors, staff and academic leaders to support data-informed decisions that enhance teaching and learning.

Across projects, the Analyst will consult with specialists on the data-driven design of student learning initiatives producing reports and analyses, and will have the opportunity to build new data tools that improve the student learning experience. The ideal candidate is comfortable working with stakeholders to understand their needs, brings creative approaches to interpreting learning data through analysis and visualization. This includes experience querying databases (SQL) coding using a programming language (e.g., R or Python) and a data visualization tool (e.g., Tableau or Power BI).

Your responsibilities will include:

• Creating and producing visual images on scientific data and research
• Analyzing and developing program scripts to extract, reformat and analyze data
• Developing and maintaining a dashboard for quick access to key performance indicators
• Communicating and presenting results to technical and non-technical audiences
• Analyzing complex data that requires great precision and attention to many details
• Generating reports
• Coordinating tasks for projects and other strategic initiatives with stakeholders

Essential Qualifications:

• Bachelor's Degree or acceptable combination of equivalent experience.
• Minimum five years of relevant experience supporting data-driven decision-making by conducting detailed data analysis, producing complex statistical information, and analyzing large datasets, preferably in a postsecondary education or research-intensive institution
• 2+ Years experience developing visualizations using Tableau or Power BI
• Experience developing and maintaining a dashboard of key performance indicators.
• Experience and intermediate skills in writing/coding programming scripts (e.g. Python, SQL) to extract, reformat, and analyze data.
• Experience effectively synthesizing information
• Experience training on research methods and data analysis
• Experience working with and manipulating complex data sets using Excel, Tableau and R
• Experience with data analysis.
• Familiarity with Microsoft Office products, and advanced skills in Microsoft Excel.
• Strong oral and written communication and presentation skills.
• Excellent organizational and time-management skills, with the ability to adapt to new and changing priorities
• Project management skills with demonstrated ability to meet deadlines and to manage a set of competing priorities.
• Demonstrated strong client service orientation and commitment to fostering equity, diversity and inclusion in a professional environment.

To be successful in this role you will be:

• Meticulous
• Multi-tasker
• Organized
• Persuasive
• Problem solver
• Self-directed

Closing Date: 10/19/2026, 11:59PM ET
Employee Group: USW 
Appointment Type : Budget - Continuing 
Schedule: Full-Time
Pay Scale Group & Hiring Zone:
USW Pay Band 13 -- $89,794 with an annual step progression to a maximum of $114,832. 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: Voir email sur jobs.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.