Data Scientist – Transmission ROW Risk Analytics

About the role

We are looking for a highly analytical Data Scientist to develop quantitative risk analysis and predictive analytics for Transmission Right‑of‑Way (ROW) risk reduction. The role will translate field, asset and operational data into actionable insights that help prioritize encroachments and prevent safety, reliability and wildfire events.

Key responsibilities

• Design and implement quantitative risk frameworks, defining risk equations, scoring methodologies and analytical models to estimate event likelihood and consequences.
• Build predictive models using statistical and machine learning techniques to forecast safety or reliability incidents related to transmission ROW encroachments.
• Apply logistic regression, survival analysis, random forests, gradient boosting, Bayesian methods, scenario modeling and simulation to identify leading risk indicators.
• Develop geospatial and spatiotemporal models that incorporate proximity to energized assets, encroachment type, clearance deficits, land‑use patterns, historical incidents and environmental conditions.
• Collaborate with cross‑functional teams—including electric operations, asset management, vegetation management, engineering, GIS and program management—to integrate data and deliver insights to business and executive stakeholders.

Required profile

• Strong analytical mindset with experience in quantitative risk modeling and predictive analytics.
• Ability to work in complex operational environments and communicate technical findings to non‑technical audiences.
• Experience partnering with multidisciplinary teams to translate data into business decisions.

Required skills

• Statistical modeling
• Machine learning
• Logistic regression
• Survival analysis
• Random forests
• Gradient boosting
• Bayesian methods
• Scenario modeling
• Simulation
• Geospatial modeling
• Spatiotemporal modeling