Job ID: 63897
Job Category: Engineering & Technical
Division & Section: Toronto Water, Technology & Customer Experience
Work Location: 60 Tiffield Road
Job Type & Duration: Full Time, Temporary (12 month) Vacancy
Salary Range: $89,337.00 -$132,880.00, TM5110, wage grade PTM2
Shift Information: 35 hours per week
Affiliation: Non-Union
Number of Positions Open: 1
Posting Period: 31-Aug-2026 to 15-Sep-2026
Major Responsibilities:
- Implements detailed plans and recommends policies/procedures regarding program specific requirements.
- Supervises, motivates and trains assigned staff, ensuring effective teamwork, high standards of work quality and organizational performance, continuous learning and encourages innovation in others.
- Supervises the day to day operation of all assigned staff including the scheduling, assigning and reviewing of work. Authorizes and coordinates vacation and overtime requests. Monitors and evaluates staff performance, approves salary increments, hears grievances and recommends disciplinary action when necessary.
- Provides input into and administers assigned budget, ensuring that expenditures are controlled and maintained within approved budget limitations.
- Leads tasks and projects related to the modelling, analysis, and interpretation of divisional and other spatial datasets.
- Designs, tests, and builds complex models to solve complex divisional analytics problems, identifying opportunities for using advanced statistical and predictive modelling techniques.
- Investigates and implements cutting edge machine learning techniques.
- Develops, implements, and evaluates work plans for divisional data projects and tasks.
- Explores, analyses, and advises the Team Lead and Manager on the value and applications of, and challenges associated with, emerging datasets.
- Works with various research methods.
- Builds processes and methods to ingest and analyze large datasets from structured and unstructured data sources such as GPS-probe data, sensor-based data, and other large datasets.
- Conducts peer and literature reviews on novel modelli