The position leads cross-functional efforts to develop predictive intelligence platforms that integrate SCADA, AMI, DER, outage, weather, and asset data to identify emerging risks and improve system reliability. Responsible for establishing technical frameworks, analytical methodologies, and best practices, the role supports reliability improvement initiatives, risk-informed investment planning, and grid modernization efforts. Through collaboration with engineering, operations, asset management, and technology teams, the position delivers actionable insights that improve reliability performance, reduce operational risk, and support achievement of key reliability objectives, including SAIDI, SAIFI, and resilience targets.
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.
PG&E is providing the salary range that the company, in good faith, believes it may pay for this position at the time of the job posting. This compensation range is specific to the job's locality. The actual salary paid to an individual will be based on multiple factors, including, but not limited to, specific skills, education, licenses or certifications, experience, market value, geographic location, collective bargaining agreements, and internal equity. Although we estimate the successful candidate hired into this role will be placed toward the middle or entry point of the range, the decision will be made on a case-by-case basis, taking these factors into account. This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.
A reasonable salary range is
- Bay Area Minimum: $105,000
- Bay Area Mid-Point: $137,000
- Bay Area Maximum: $169,000
Job Responsibilities
- Maintains and updates simple analytical models and assumptions for larger analytical projects.
- Completes complex quantitative modeling and analysis with limited support.
- Clearly articulates recommendations and findings in both written and oral communications both internally and externally.
- Works with other utilities and industry groups in the development of new and innovative data and quantitative models, research, etc.
- 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.
Qualifications
Minimum
Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, Business or equivalent field
4 years of job-related experience
OR Master’s Degree and 3 years’ job-related experience
OR Doctorate and 1 year of job-related experience
Desired
- Master’s degree or equivalent experience in Power System Engineering
- Job-related experience, 6 years
