Research Methods Specialist - Education Evaluation

Education at CAMH is seeking a full-time, temporary (until April 30, 2027) Research Method Specialist (RMS) to support evaluation research and quality improvement. The RMS will report to the Manager Education Evaluation and Quality Improvement and will work with diverse stakeholders, including staff, partners, families and patients will support the development and implementation of evaluation and data projects utilizing evidence-based evaluation approaches, frameworks and metrics.

The Research Methods Specialists will build and implement evaluation plans for community-based and system change initiatives, using a variety of different evaluation tools (such as logic models, theories of change, evaluation frameworks, data support systems and monitoring reporting tools).

The incumbents will also have experience using a variety of evaluation approaches, such as developmental, empowerment, formative, and summative evaluation.

In particular, the RMS will work to design rigorous evaluations constructs to measures and track the progress of Collaborative Learning College (CLC) using both quantitative and qualitative methodologies. Using principles of co-production, the work will include to develop evidence-based measures, conduct scoping reviews, and collect, analyze & disseminate process and outcome data through surveys, focus groups, and other methods in consultation with CLC stakeholders.

The RMS will also be involved in supporting the development of a single database for all education evaluation data, conducting natural language processing and artificial intelligence informed algorithms, conducting predictive modelling and using similar data science techniques/ models to measure broader education outcomes for quality improvement, communication and dissemination.

This position offers an exciting opportunity for a highly motivated, organized and hard-working individual with strong research/evaluation, interpersonal and communication skills, especially in advanced quantitative analytical skills who can work independently and within a team as required. This position is located at 1025 Queen Street West.

The successful candidate will have an Honors Bachelor’s degree in a relevant discipline including social or behavioural sciences, Health Informatics, Public Health, psychometric or a related social science degree, combined with 5 years of relevant experience. Research or evaluation experience in a health sciences or education research environment is required. Experience in coordinating and analyzing big data using R or Python is essential, including experience in algorithm development, construction of validated scales, database management and the use of machine learning.

Knowledge and understanding of qualitative and quantitative research methods is required. The candidate will have excellent communication(oral and written), creative problem-solving abilities and organizational skills. The ability to manage and adapt to diverse work environments and conditions is essential. Candidates require the ability to work effectively with individuals from diverse backgrounds. Bilingualism (French/English) or proficiency in a second language would be an asset.

Salary Range: $42.67 – $57.55 per hour

If you are interested in this position, please ensure that you apply before 5pm EST of the closing date. If your application is received past 5pm EST of the closing date, your application will not be accepted.

CAMH is a fully affiliated teaching hospital and research institute of the University of Toronto. As a CAMH employee, you will contribute to our mission by supporting teaching, research, and clinical care across the hospital.

CAMH is dedicated to equity, diversity, and inclusion. Our commitment is to foster a workplace, teaching, and learning environment that is inclusive, respectful, and free from discrimination or harassment.

CAMH strongly encourages applications from candidates who reflect the diversity of the communities we serve, including First Nations, Métis, and Inuit Peoples; Black and other racialized communities; LGBTQ2S+ communities; women; and people with disabilities, including those with lived experience of mental health and substance use challenges.

We welcome applicants from all backgrounds. Thank you to all who apply; however, only those selected for an interview will be contacted. If you require accommodations during the application or recruitment process, please let us know.