Principal Quantitative Analyst

Requisition ID # 166379

Job Category: Business Operations / Strategy; Engineering / Science

Job Level: Manager/Principal

Business Unit: Electric Engineering

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. This team of forward–thinking individuals will be tasked with deploying technology and infrastructure and influencing the organization to achieve the company’s reliability goals. The team is responsible for implementing programs required to modernize the electric grid allowing for safe, resilient and efficient operations. The team participates in a cross functional team of internal and consulting participants being tasked with leading the transition of a project from development and testing to being operational for each phase of each project.

Position Summary

Within the System Performance, Reliability and Resiliency Strategy team, this position reports to the Senior Manager of Reliability Programs and is responsible for developing advanced data science models, prediction tools, and industry-leading anomaly detection techniques to identify potential failures and enhance the reliability of the electric transmission and distribution grid.

The principal quantitative analyst ensures the safe, reliable and efficient operation of the electric power system by providing innovative engineering and advanced reliability analysis support to the team of senior engineers, scientist and program managers responsible for developing projects and solutions to improve system reliability and resiliency.

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, 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.​

A reasonable salary range is:

Minimum Base Salary (Bay Area) $144,000.00

Mid Base Salary (Bay Area) $194,000.00

Maximum Base Salary (Bay Area) $244,000.00

Responsibilities Lead research and development of state-of-the-art methodologies to detect potential system failures and improve the reliability of the electric transmission and distribution grid. Applies data science/ machine learning /artificial intelligence methods to develop defensible and reproducible models, Serves as the technical lead for the development of predictive/reliability analytics models. Develops python codes for data processing and data science model developments (e.g., ML/AI models, advanced statistical models) Documents datasets, modeling processes, and result to ensure transparency, reproducibility, and defensibility. Contribute to the development of data science strategies aligned with system performance, reliability, and resiliency team goals. Communicate technical concepts and model results to internal/external stakeholders. Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis. Works with sponsor departments and company subject matter experts to understand the application and potential of data science solutions that create value. Act as peer reviewer of complex models Works autonomously. Anticipates issues and develops innovative solutions. Demonstrates program leadership with internal & external stakeholders to support company goals. May design and develop new, complex programs. May manage major cross-functional projects and initiatives. May lead initiatives that impact utility or industry developments. Manages all aspects of programs that are cross functional, complex, of broad scope and have a significant financial or political impact on the line of business. Partners with leadership determine the most appropriate and effective program performance metrics. Develops content and format for reports and dashboards. Prepares and presents regular updates to senior management, addressing issues and gaining buy in on solutions. Reviews and approves the maturity for release of technical features in data science products. Identifying trends and focus areas based on asset classes, regions, etc

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

Desired: Doctorate degree with 5+ years or master’s degree with 8+ years in Engineering, Operations Research, Applied Sciences, Statistics, or job-related discipline or equivalent experience Develops and evaluates advanced quantitative tools and examines alternate solutions to a problem, effectively troubleshoots various issues and analysis, and provides findings and recommendations for internal clients and external stakeholders. Hands-on and theoretical experience in developing and deploying data science and ML models using Python. Proven ability to formulate and solve unstructured, complex problems using data-driven approaches. Proficiency in working with large datasets, including structured and unstructured data from diverse sources. Proactively identifies future challenges and is responsible for innovating existing models and analytical assumptions of the highest complexity. Manages and builds consensus for major cross-functional and cross company projects and initiatives. Demonstrated ability to take a conceptual issue and independently design and complete innovative analysis to draw meaningful conclusions. Works with all levels of leadership (up to and including executives) across functions 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. Excellent communication skills, with the ability to explain technical concepts to non-technical audiences. Ability to develop, coach and teach career level Analysts and data scientists in data science/artificial intelligence/machine learning techniques and technologie s