Decision Support Analyst; Industrial Engineer

UHN is Canada’s #1 hospital and the world’s #1 publicly funded hospital. With 10 sites and more than 44,000 TeamUHN members, UHN consists of Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute, The Michener Institute of Education and West Park Healthcare Centre. As Canada's top research hospital, the scope of biomedical research and complexity of cases at UHN have made it a national and international source for discovery, education and patient care.

UHN has the largest hospital-based research program in Canada, with major research in neurosciences, cardiology, transplantation, oncology, surgical innovation, infectious diseases, genomic medicine and rehabilitation medicine. UHN is a research hospital affiliated with the University of Toronto.

UHN’s vision is to build A Healthier World and it’s only because of the talented and dedicated people who work here that we are continually bringing that vision closer to reality.

Union: Non-Union
Number of vacancies: 1
New or Replacement Position: New
Site: Toronto General Hospital
Department:Data & Analytics
Reports to: Manager, Data & Analytics
Salary Range: $35.35 to $53.03 per hour
Hours:37.5 hours per week
Status: Temporary Full-Time
Closing Date:August 31, 2026

UHN Data & Analytics supports UHN’s growing demand for data and data-driven insights, helping TeamUHN ensure the needs of patients come first. Our collective goal is to better see, understand, and use data to help UHN become a data-driven organization, advance strategic priorities, and improve care, research, and education. UHN Data & Analytics supports data-driven decision-making, performance improvement, data governance, analytics, and automation through collaboration across the organization.

The Decision Support Analyst (Industrial Engineer) will play a key role in supporting resource management analysis across UHN. With a strong industrial engineering background, the successful candidate will apply industrial engineering methods, operational analytics, and data-driven problem solving to assess capacity, demand, workflow, staffing, productivity, and resource utilization. This role requires strong analytical and process improvement skills, expertise in data analysis and visualization tools, and the ability to translate complex operational data into practical recommendations that support planning, performance improvement, and decision-making.

• Conduct resource management analysis to assess capacity, demand, staffing, workload, productivity, utilization, and service performance across clinical and operational areas.
• Apply industrial engineering methods, including process mapping, workflow analysis, time-and-motion concepts, queueing principles, simulation, optimization, and productivity analysis, to identify improvement opportunities.
• Develop, maintain, and enhance decision support tools, models, reports, and dashboards that support resource planning, operational performance monitoring, and evidence-based decision-making.
• Partner with clinical programs, operational leaders, finance, and data teams to define business questions, translate operational needs into analytical approaches, and support implementation of recommendations.
• Analyze trends, variances, constraints, and drivers of resource use to support workforce planning, service planning, throughput improvement, and performance management.
• Prepare clear presentations, briefing materials, and recommendations for stakeholders at all levels, translating complex analysis into practical insights and actionable options.
• Build and apply analytical models to evaluate capacity constraints, resource allocation options, staffing scenarios, service demand, and operational trade-offs.
• Support scenario planning, forecasting, and sensitivity analysis to help leaders understand the operational impact of changes in volume, staffing, schedules, models of care, or service delivery.
• Work with stakeholders to validate data sources, assumptions, definitions, and methodology to ensure analyses are accurate, transparent, and aligned with operational realities.
• Monitor the impact of operational and resource…