WPR-28330
Data Science & Analytics
Published project
Project Budget
USD 64,000 – 92,000
Enterprise Data Science & Analytics Execution & Implementation
A utility needs a better way to prioritize inspections across lines, substations and access roads exposed to wildfire conditions. The engagement will combine operational asset data with weather, vegetation and terrain signals to produce a defensible risk model for the next fire season.
Industry Sector
General Industry
Work Arrangement
remote (Toronto)
Project Sourcing
WPR-28330 (Project reference)
Published Date
8/24/2026
Detailed Scope of Work & Deliverables
DETAILED SCOPE & MILESTONES
1. Audit asset coordinates, inspection history, outage records and available environmental datasets; document gaps that
could distort risk rankings.
2. Create the geospatial feature set and baseline scoring method, then compare statistical and machine-learning approaches
with operations staff.
3. Build an interactive map and weekly risk queue that explains why each asset has been prioritized rather than returning an
opaque score.
4. Back-test results against prior incidents, set refresh procedures and hand over code, data dictionaries and an operating
playbook.
Required Competencies & Skills
Data ScienceData AnalyticsData EngineeringBusiness IntelligencePower BISQL
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