Job Description

Date Posted: 05/03/2023
Req ID: 31041
Faculty/Division: VP & Provost
Department: Centre for Teaching Support & Innovation
Campus: St. George (Downtown Toronto)
Position Number: 00041683

Description:

About us:

The Centre for Teaching Support & Innovation (CTSI) provides leadership in teaching and learning at the University of Toronto and serves as the University\xe2\x80\x99s central teaching \xe2\x80\x9chub\xe2\x80\x9d. In a dynamic and highly collaborative environment, CTSI provides support for pedagogy and pedagogy-driven instructional technology for all teaching staff and teaching assistants across the University\xe2\x80\x99s campuses and divisions. Its services include organizing special events and programming for instructors and teaching assistants related to a range of teaching topics, including educational technologies; conducting personalized and confidential consultations; offering job training and a certificate program for teaching assistants; supporting inquiry into teaching through the Scholarship of Teaching and Learning; providing pedagogical guidance for the use of the institutional learning management system (Quercus); and supporting the institutional online course evaluation system. Driven by the latest advancements in higher education practices and informed by emerging research in post-secondary teaching and learning, CTSI staff work directly with faculty, graduate students, departments and divisions and in partnership with a range of University offices to enhance teaching and learning across the institution.

Your opportunity:

Under the general direction of the Director and Associate Director, CTSI and supervision of the Manager, Evaluation & Assessment, the Data Analyst, Course Evaluation, will be an integral member of the Evaluation & Assessment team. The incumbent is responsible for performing complex statistical analyses and research work in collaboration with the SoTL team and Course Evaluation Operation team at CTSI. The incumbent will work primarily with course evaluation data collected through the online course evaluation system and framework, as well as analytics and surveys conducted in support of these efforts. The Data Analyst, Course Evaluations will contribute to ongoing quality improvement and evaluation by contributing to research reports and papers, workshops and presentations, and resources for academic leadership, faculty and students.

Your responsibilities will include:

• Analyzing complex data that requires attention to detail and statistical best practices
• Producing complex statistical information using multivariate statistical analyses in R, Python, and/or SAS
• Analyzing and developing program scripts to extract, reformat and analyze datasets and data flow in R, Python, SAS, and/or SQL
• Planning and developing strategic goals and overall activities for research projects independently as well as collaboratively
• Writing research summaries for reporting purposes for a range of stakeholders and audiences
• Creating and producing visual images for scientific data and research reports/dashboards
• Conducting literature reviews
• Developing content for and leading workshops and presentations

Essential Qualifications:

• Bachelor\'s Degree with emphasis on quantitative research methodologies (including statistics), or an acceptable equivalent combination of education and experience.
• Minimum (5) five years\' relevant experience with data wrangling & analysis, preferably within a higher education setting, or related public sector environment
• Strong data wrangling and analysis skills with complex data: ability to carry out a variety of multivariate statistical analyses including modelling (e.g., multiple regression, mixed models) and evaluating reliability and validity (e.g., factor analyses), experience writing research summaries and presenting the results in both written and presentation form.
• Demonstrated ability to prepare and present reports for senior management and senior institutional leaders, complete systematic literature searches and summaries.
• Strong technical skills: advanced understanding of data management, statistical software, and data.
• Demonstrated advanced knowledge of statistical applications such as R, Python, or SAS.
• Intermediate knowledge of Excel, PowerPoint, and Word.
• Strong interaction skills: oral and written communication skills to develop meaningful visualisations and to explain complex statistical analyses to decision makers and other stakeholders, probe for information to establish needs and respond to data requests.
• Strong interpersonal skills, highly collaborative, having the ability to work independently and as part of a team.
• Experience working in a collaborative team-based environment

Assets (Nonessential):

• Educational background in Psychometrics, Education Psychology, Statistics, or related field and/or experience with a wide range of different statistical analyses and approaches
• Ideally, formal training and research experience in test measurement and assessment theories such as Classical Test Theory and Item Response Theory.
• Experience in survey validation
• Familiarity with qualitative research methodologies (interviews, focus groups, etc.)

To be successful in this role you will be:

• Communicator
• Efficient
• Meticulous
• Organized
• Problem solver
• Team player

Closing Date: 05/16/2023, 11:59PM ET
Employee Group: USW
Appointment Type: Budget - Continuing
Schedule: Full-Time Occasional overtime on weekends.
Pay Scale Group & Hiring Zone:
USW Pay Band 13 -- $76,284 with an annual step progression to a maximum of $97,556. Pay scale and job class assignment is subject to determination pursuant to the Job Evaluation/Pay Equity Maintenance Protocol.
Job Category: Administrative / Managerial
Recruiter: Anita Chooraman

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.

University of Toronto