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

Pacific Gas And Electric Company•Oakland, CA

1d•$140,000 - $251,000•Hybrid

About The Position

The Principal 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.

Requirements

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 8 years, OR Master’s Degree and 7 years of job-related, OR Doctorate and 5 years

Nice To Haves

Advanced Degree
Job-related experience 10 years
Expertise and thought leadership 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
Demonstrated ability to lead large and complex projects working with cross-functional teams
Excellent oral and written communication skills and ability to concisely and strategically convey information based on unique audience needs
Demonstrated capability in planning and prioritizing work to meet commitments aligned with organizational goals
Demonstrated integration of LEAN principles into work practices

Responsibilities

Manages and builds consensus for major cross-functional and cross-company projects and initiatives. Works with all levels of leadership (up to and including executives) across functions to defend findings and recommendations to influence decisions.
Develops industry-wide best practices and works with other utilities and industry groups in the development of new and innovative data and quantitative models and research.
Develops and evaluates advanced quantitative tools and examines alternative solutions to a problem, effectively troubleshoots various issues and analyses, and provides findings and recommendations for internal clients and external stakeholders.
Proactively identifies future challenges and is responsible for innovating on existing models and analytical assumptions of the highest complexity.
Coaches, mentors, and trains others.
Influences policy and program strategy at other utilities and regulatory agencies.
Sponsors testimony on complex analysis and policy issues.
Provides critical and insightful assessments of third-party work products and comparisons to internal work products.
Identifies and implements opportunities to improve business processes.
Develops and maintains relationships with various internal and external stakeholders regarding quantitative modeling and analysis, and represents PG&E at various external forums.
Creates data mining architectures, models, protocols, statistical reporting, and analytical methodologies to identify trends and failure patterns in structured and unstructured datasets.
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.