Senior, Quantitative Analyst: Asset Failure Analysis, Electric Asset Strategy (Flexible location)

Pacific Gas and Electric Company; Oakland (CA); Hybrid; USD 100,000 - 169,000; Full time

Job summary

Pacific Gas and Electric Company seeks a Senior Quantitative Analyst to apply advanced analytics to asset performance and failure analysis within Electric Asset Strategy. You will build scalable models, leverage Python/SQL and Palantir Foundry, and collaborate with cross-functional teams to drive risk-informed decisions.

The role emphasizes developing defensible analytical solutions, translating insights into actionable steps for asset management, and contributing to AI/ML initiatives to enhance

Qualifications

• Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, Business or equivalent field.
• Job-related experience: 4 years
• OR Master’s Degree and 3 years of job-related experience
• OR Doctorate and 1 year
• Desired: Job-related experience: 6 years

Responsibilities

• Researches and applies knowledge of existing and emerging data science principles, theories, and techniques to inform engineering and business decisions related to electric distribution asset performance.
• Creates data mining architectures, models, protocols, statistical reporting, and analytical methodologies to identify trends and failure patterns in structured and unstructured datasets.
• Extracts, transforms, and loads data from dissimilar sources across PG&E to support feature engineering and analytical workflows.
• Applies data science, machine learning, and artificial intelligence methods to develop defensible, reproducible predictive or optimization models supporting asset failure analysis and risk mitigation.
• Partners with engineers, asset managers, compliance, inspections, wildfire risk and operations teams to ensure analytical outputs are actionable and aligned with electric distribution system design, operation, and maintenance.
• Serves as the technical lead for the development of discrete analytical models and solutions, ensuring sound methodology and clear documentation.
• Develops and presents complex analytical topics in a clear, concise manner to employees and stakeholders at various levels of the organization.

Skills

Quantitative analytics

Data mining

Statistical analysis

Communication (oral and written)

Education

Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, Business or equivalent field

Job-related experience: 4 years

Master’s Degree and 3 years of job-related experience

Doctorate and 1 year

Desired: 6 years of job-related experience

Tools

Python

SQL

Palantir Foundry

BI tools

Job description

Requisition ID# 175116

Job Category: Business Operations / Strategy

Job Level: Individual Contributor

Business Unit: Energy Delivery

Work Type: Hybrid

Job Location: Oakland; Alameda; Alta; American Canyon; Angels Camp; Antioch; Auberry; Auburn; Avenal; Avila Beach; Bakersfield; Balch Camp; Bay Point; Bear Valley; Belden; Bellota; Belmont; Benicia; Berkeley; Brentwood; Brisbane; Buellton; Burney; Buttonwillow; Calistoga; Campbell; Canyon Dam; Canyondam; Capitola; Caruthers; Chico; Clearlake; Clovis; Coalinga; Colusa; Concord; Concord; Corcoran; Cotati; Cottonwood; Cupertino; Daly City; Danville; Davis; Dinuba; Downieville; Dublin; Emeryville; Eureka; Fairfield; Folsom; Fort Bragg; Fortuna; Fremont; French Camp; Fresno; Fresno; Fulton; Garberville; Geyserville; Gilroy; Goodyear; Grass Valley; Guerneville; Half Moon Bay; Hayward; Hinkley; Hollister; Holt; Houston; Huron; Jackson; Kerman; King City; Lakeport; Lemoore; Lincoln; Linden; Livermore; Lodi; Loomis; Los Banos; Lower Lake; Madera; Magalia; Manteca; Manton; Mariposa; Martell; Marysville; Maxwell; Menlo Park; Merced; Meridian; Millbrae; Milpitas; Modesto; Monterey; Montgomery Creek; Morgan Hill; Morro Bay; Moss Landing; Mountain View; Napa; Needles; Newark; Newman; Novato; Oakdale; Oakhurst; Oakley; Olema; Orinda; Orland; Oroville; Palo Alto; Palo Cedro; Paradise; Parkwood; Paso Robles; Petaluma; Pioneer; Pismo Beach; Pittsburg; Placerville; Pleasant Hill; Pleasanton; Point Arena; Potter Valley; Quincy; Rancho Cordova; Red Bluff; Redding; Richmond; Ridgecrest; Rio Vista; Rocklin; Roseville; Round Mountain; Sacramento; Salida; Salinas; San Bruno; San Carlos; San Francisco; San Francisco; San Jose; San Luis Obispo; San Mateo; San Rafael; San Ramon; San Ramon; Sanger; Santa Cruz; Santa Maria; Santa Nella; Santa Rosa; Selma; Shaver Lake; Sonoma; Sonora; South San Francisco; Springville; Stockton; Storrie; Taft; Tracy; Turlock; Twain; Ukiah; Vacaville; Vallejo; Walnut Creek; Wasco; Washington; Watsonville; West Sacramento; Wheatland; Whitmore; Willits; Willow Creek; Willows; Windsor; Winters; Woodland; Yuba City

Department Overview

Welcome to Electric Asset Strategy (EAS). We are responsible for the Distribution electric system’s asset strategy, standards, procedures and end-to-end risk management for 2.3 million structures. We deliver a risk informed strategic plan, leveraging inspection insights and asset data to drive strategic maintenance and investment decisions.

The Distribution Asset Risk Management (ARM) team—comprising Asset Failure Analysis (AFA), Asset Insights, and Inspections & Maintenance Strategy (I&M)—focuses on continuously improving on how PG&E monitors and maintains its assets to support a resilient, reliable grid to help keep our communities safe.

Position Summary

The Senior Quantitative Analyst will apply advanced quantitative analytics techniques to support electric distribution’s advancement of asset insights, with a focus on identifying equipment failure causes, detecting adverse performance trends, and enabling data-driven insights and engineering-focused risk mitigation strategies. This role will support the Asset Failure Analysis (AFA) team by developing scalable, defensible, and reproducible analytical solutions using structured and unstructured data from across PG&E.

The successful candidate will bring strong technical expertise and be comfortable working across a modern analytics stack, including Python, SQL, Palantir Foundry, and business intelligence tools. This role will also contribute to the adoption and implementation of artificial intelligence and machine learning solutions to enhance, streamline, and automate aspects of asset failure review, trend detection, and decision support.

Possessing passion for data analytics and advancement of electric utility asset management concepts is critical. Your quantitative expertise will enable the Senior Data Scientist to quickly translate analytical insights into practical actions that will align with how electric distribution systems are designed, operated, and maintained. If you are seeking a challenging role that has a real impact in making California safer, come join our team.

Job Responsibilities

• Researches and applies knowledge of existing and emerging data science principles, theories, and techniques to inform engineering and business decisions related to electric distribution asset performance.
• Creates data mining architectures, models, protocols, statistical reporting, and analytical methodologies to identify trends and failure patterns in structured and unstructured datasets.
• Extracts, transforms, and loads data from dissimilar sources across PG&E to support feature engineering and analytical workflows.
• Applies data science, machine learning, and artificial intelligence methods to develop defensible, reproducible predictive or optimization models supporting asset failure analysis and risk mitigation.
• Partners with engineers, asset managers, compliance, inspections, wildfire risk and operations teams to ensure analytical outputs are actionable and aligned with electric distribution system design, operation, and maintenance.
• Serves as the technical lead for the development of discrete analytical models and solutions, ensuring sound methodology and clear documentation.
• Develops and presents complex analytical topics in a clear, concise manner to employees and stakeholders at various levels of the organization.

Compensation

PG&E is providing the salary range that the company in good faith believes it might pay for this position at the time of the job posting. This compensation range is specific to the locality of the job. 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 towards the middle or entry point of the range, the decision will be made on a case-by-case basis related to these factors. 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
&/OR
CA Minimum: $100,000
CA Mid-Point: $130,000
CA Maximum: $161,000

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.
• Job-related experience: 4 years
• OR Master’s Degree and 3 years of job-related experience
• OR Doctorate and 1 year
• Desired:
• Job-related experience: 6 years

Knowledge, Skills, Abilities, and Technical Competencies:

• Expertise in quantitative energy system modeling and analysis frameworks and techniques.
• Knowledge of data science, machine learning, operations research, engineering, or economics analytical modeling tools and programming languages.
• Experience at electric or natural gas utilities, independent power producers, wholesale energy market participants, regulatory agencies, consulting firms, or similar organizations
• Demonstrated ability to take a conceptual issue and independently design and complete innovative analysis to draw meaningful conclusions.
• Strong oral and written communication skills and ability to concisely convey information based on unique audience needs.
• Capability in planning and prioritizing work to meet commitments aligned with organizational goals.