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About the Role
CAMH Education is seeking a 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 to support the development and implementation of evaluation and data projects utilizing evidence-based evaluation approaches, frameworks and metrics.
Responsibilities
- Build and implement evaluation plans for community-based and system change initiatives using various evaluation tools.
- Design rigorous evaluations to measure and track the progress of Collaborative Learning College (CLC) using quantitative and qualitative methodologies.
- Develop evidence-based measures, conduct scoping reviews, and collect, analyze, and disseminate process and outcome data.
- Support the development of a single database for all education evaluation data.
- Conduct natural language processing and artificial intelligence informed algorithms.
- Perform predictive modeling and use similar data science techniques to measure broader education outcomes for quality improvement, communication, and dissemination.
Requirements
- Honors Bachelor’s degree in a relevant discipline (social or behavioural sciences, Health Informatics, Public Health, psychometric or a related social science degree).
- 5 years of relevant experience.
- Research or evaluation experience in a health sciences or education research environment.
- Experience coordinating and analyzing big data using R or Python.
- 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.
- Excellent communication (oral and written) abilities.
- Creative problem-solving abilities.
- Organizational skills.
- Ability to manage and adapt to diverse work environments and conditions.
- Ability to work effectively with individuals from diverse backgrounds.
- Bilingualism (French/English) or proficiency in a second language is an asset.
Skills
- Logic models
- Theories of change
- Evaluation frameworks
- Data support systems
- Monitoring reporting tools
- Developmental evaluation
- Empowerment evaluation
- Formative evaluation
- Summative evaluation
- Quantitative methodologies
- Qualitative methodologies
- Co-production principles
- Scoping reviews
- Surveys
- Focus groups
- Natural language processing
- Artificial intelligence
- Predictive modelling
- Data science techniques
- R
- Python
- Algorithm development
- Validated scales construction
- Database management
- Machine learning
Location
- 1025 Queen Street West
Work Type
- Full-time
- Temporary (until April 30, 2027)
Experience Level
- 5 years of relevant experience
Education Level
- Honors Bachelor’s degree in a relevant discipline
Salary/Compensations
- $42.67 – $57.55 per hour
About the Company
- CAMH is a fully affiliated teaching hospital and research institute of the University of Toronto.
- CAMH is dedicated to equity, diversity, and inclusion.
- CAMH is implementing its Strategic Plan: Connected CAMH, to transform lives, ignite innovation and discovery, revolutionize education and drive social change.
- CAMH is on a mission to change the way society thinks about and responds to mental illness.
- CAMH aims to eliminate prejudice and discrimination and shape a world where mental illness is central to our healthcare system – a world where Mental Health is Health.
- To learn more about CAMH, please visit their website at: www.camh.ca.
Equal Opportunity
- 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.
- If you require accommodations during the application or recruitment process, please let us know.