Data Analyst, Course Evaluations

University of Toronto

The Centre for Teaching Support & Innovation (CTSI) at the University of Toronto leads efforts in teaching and learning, operating as a pivotal educational hub. Within this collaborative environment, they support pedagogy and instructional technology across campuses, working with faculty, students, and various departments to enhance educational practices. This role exists to contribute significantly to the evaluation and quality improvement of course evaluations and educational assessments.

In this role you can expect to have the responsibilities:

• Perform complex data analysis with a focus on detail and statistical best practices.
• Utilize multivariate statistical analyses in R, Python, and SAS to produce insights.
• Develop scripts to extract and analyze datasets using R, Python, SAS, and SQL.
• Plan and execute strategic goals for research projects both independently and collaboratively.
• Write and present research summaries for varied stakeholders.
• Create visual representations for scientific data and dashboards.
• Conduct literature reviews.
• Develop and lead workshops and presentations.

This role comes with the following benefits:

• Opportunities for professional development and learning encouragement.

This role requires you to have:

• Bachelor's degree focused on quantitative research methodologies or equivalent experience.
• A minimum of 5 years' experience in data analysis within higher education or public sector.
• Strong skills in data wrangling and multivariate statistical analysis.
• Advanced proficiency in R, Python, and SAS.
• Intermediate proficiency in Excel, PowerPoint, and Word.
• Strong oral and written communication skills.
• Ability to work independently and within a team.

You would benefit from having:

• Background in Psychometrics or Educational Psychology.
• Experience with Classical Test Theory and Item Response Theory.
• Survey validation experience.
• Familiarity with qualitative research methodologies.

The University of Toronto encourages candidates from Indigenous, Black, racialized, and 2SLGBTQ+ communities or those with disabilities to apply, as these experiences will be considered in the evaluation of candidates.