Expert, Quantitative Power System Analyst

Department Overview

The System Performance, Reliability and Resiliency Strategy team within the overall Electric Transmission and Distribution Engineering organization is responsible for planning, organizing, and managing the resources necessary to successfully execute PG&E's Electric Reliability Strategy and initiatives. Within this department the Resiliency Strategy and Partnerships team will lead the long‑term reliability and resiliency strategy. This work will include driving the development of tools and processes that proactively estimate and anticipate grid conditions at the circuit level to provide a more resilient electric grid.

This position serves as the utility's leading technical expert for predictive grid intelligence, Distribution System State Estimation (DSSE), and advanced reliability analytics. The role establishes the vision, strategy, and technical direction for state‑aware grid management, enabling the transition from reactive operations to proactive, predictive decision‑making. Leveraging machine learning, artificial intelligence, physics‑based modeling, and digital twin technologies, the position delivers real‑time and forecasted insights into system performance, asset health, operational risk, and reliability outcomes across an increasingly dynamic and decentralized electric grid.

As a recognized industry authority, the role leads the development of enterprise‑wide predictive intelligence platforms that integrate SCADA, AMI, DER, outage, weather, and asset data to forecast grid conditions and identify emerging risks before failures occur. The position establishes technical standards and best practices for digital grid modeling, forecasting, and advanced analytics while driving measurable improvements in reliability, resilience, risk reduction, and capital effectiveness.

Through innovation, industry leadership, and cross‑functional influence, the role accelerates grid modernization and supports achievement of strategic reliability objectives, including improvements in SAIDI, SAIFI, and other risk‑based performance measures.

This position follows a hybrid work model, requiring employees to report to their assigned office location at least two or three days per week. The remaining days may be worked remotely, depending on business needs. The headquarters is located in the Oakland General Office.

Salary range is:

• Bay Area Minimum: $129,000
• Bay Area Mid‑Point: $168,000
• Bay Area Maximum: $207,000

• Works independently with internal and external stakeholders with guidance on the most complex issues, development of new and innovative data and quantitative modeling, research, etc.
• Proactively identifies future challenges, develops recommendations for resolution and evaluates, and develops new analytic tools and processes for the department.
• Responsible for maintaining and updating complex models and complex analytical assumptions.
• Develops or assists in the development of industry‑wide best practices.
• Coaches, mentors, and trains others.
• Provides critical and insightful assessments of third‑party work products and comparison to internal work products.
• Lead the development and deployment of Distribution System State Estimation (DSSE) and predictive analytics capabilities to provide real‑time and forecasted visibility of grid conditions and risks at the distribution circuit level.
• Design and operationalize state‑aware grid intelligence platforms using SCADA, AMI, DER, outage, weather, and asset health data.
• Serve as an industry thought leader, driving innovation and advancing data‑driven decision‑making to improve reliability, reduce risk, and accelerate grid modernization.

• Minimum:
  • Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, Business or equivalent field
  • 6 years of job‑related experience
    • OR Master's Degree and 5 years' job‑related experience
    • OR Doctorate and 3 year of job‑related experience
• Desired:
  • Master's degree or equivalent experience in Power System Engineering
  • Job‑related experience, 8 years