Pay
$118K–$193K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
Oakland, CA, US, 94612
Open 3 months, first seen by us 110 days agoPG&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 ResponsibilitiesRead the full posting
This position serves as a senior technical leader responsible for advancing predictive grid intelligence, Distribution System State Estimation (DSSE), and reliability analytics to support a more resilient, data-driven electric system.
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.
Lead development and deployment of DSSE and predictive analytics for circuit-level grid visibility
Design and run state-aware grid intelligence platforms using SCADA, AMI, DER, outage, weather and asset data
Complete complex quantitative modeling and analysis with limited support
Maintain and update analytical models and assumptions for larger projects
Present findings and recommendations in written and oral form to internal and external audiences
This position serves as a senior technical leader responsible for advancing predictive grid intelligence, Distribution System State Estimation (DSSE), and reliability analytics to support a more resilient, data-driven electric system. The role leads the development and implementation of advanced analytical capabilities that provide real-time and forecasted visibility into system performance, asset health, and reliability risk. By applying machine learning, statistical methods, engineering analytics, and grid modeling techniques, the position enables more proactive planning, operations, and asset management decisions across the distribution network.
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.
Lead the development and deployment of Distribution System State Estimation (DSSE) and predictive analytics capabilities
Design and operationalize state-aware grid intelligence platforms using SCADA, AMI, DER, outage, weather, and asset health data.
Completes complex quantitative modeling and analysis with limited support.
Maintains and updates simple analytical models and assumptions for larger analytical projects.
Clearly articulates recommendations and findings in both written and oral communications both internally and externally.
Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, Business or equivalent field
Master’s degree or equivalent experience in Power System Engineering • Job-related experience, 6 years
4 years of job-related experience
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
- 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
- OR Master’s Degree and 3 years’ job-related experience - OR Doctorate and 1 year of job-related experience Desired:
Desired: • Master’s degree or equivalent experience in Power System Engineering • Job-related experience, 6 years
Open 3 monthsWe first saw this posting 110 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$118K–$193K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
Day 110
Up longer than most. Similar jobs usually come down between day 7 and day 56.
Well past Pacific Gas And Electric Company’s usual: its jobs come down by about day 9.
From 10,180 similar postings that came down, and 69 of Pacific Gas And Electric Company’s. Coming down is not always a hire.
9 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Requisition ID # 173278
Job Category: Business Operations / Strategy
Job Level: Individual Contributor
Business Unit: Energy Delivery
Work Type: Hybrid
Job Location: Oakland
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.
Position Summary
This position serves as a senior technical leader responsible for advancing predictive grid intelligence, Distribution System State Estimation (DSSE), and reliability analytics to support a more resilient, data-driven electric system. The role leads the development and implementation of advanced analytical capabilities that provide real-time and forecasted visibility into system performance, asset health, and reliability risk. By applying machine learning, statistical methods, engineering analytics, and grid modeling techniques, the position enables more proactive planning, operations, and asset management decisions across the distribution network.
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:
Desired:
• Master’s degree or equivalent experience in Power System Engineering
• Job-related experience, 6 years
Selected passages from the saved posting. Check the full description for conditions and exceptions.
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
Oakland, CA, US, 94612
Business Unit: Energy Delivery Work Type: Hybrid Job Location: Oakland
More relevant text appears in the full description.
No clear work-authorization passage found. Eligibility is unconfirmed.