Job Description

Requisition ID # 174570

Job Category: Accounting / Finance

Job Level: Individual Contributor

Business Unit: Strategy & Growth

Work Type: Hybrid

Job Location: Oakland

Department Overview

Over 6,500 coworkers in Electric T&D ensure the delivery of clean, safe, reliable and affordable energy to nearly 16 million people in Northern and Central California. The Electric T&D Team is responsible for ensuring the electric grid's reliability and resiliency through the ongoing maintenance and operations of PG&E's 100,000 miles of distribution lines and over 18,000 miles of Transmission lines. Coworkers in Electric T&D's actively engage in the Lean Methodology through the use of Visual Management in Operating Reviews to cross-functionally identify and solve problems, and create standard work. By working together as One Electric. One Team. We are delivering for our hometowns.

This position is headquartered in Oakland, CA.This position is "hybrid", with the expectation of being in the office 1x/week (subject to change due to business needs). This position is within the Transmission Tools and Modeling (TTM) team. TTM develops the analytical tools, data solutions, and power system models that enable informed transmission planning and operational decision-making. The team combines expertise in power system analysis, software development, data engineering, and process automation to build and maintain study cases, planning models, databases, and forecasting methodologies used across the organization. Working closely with planners, engineers, operations, and business partners, the team delivers innovative solutions that improve study efficiency, data quality, and modeling accuracy while supporting the reliable and cost-effective planning of the electric grid. The group is focused on modernizing workflows, leveraging advanced analytics, and creating scalable tools that help transform complex grid data into actionable insights.

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:​

Bay Area Minimum: $​102,000

Bay Area Maximum: $​162,000

&/OR​

California Minimum: $​97,000

California Maximum: $154,000

Position Summary

Designs, develops, and executes scripts, programs, models, algorithms, and processes, using structured and unstructured data from disparate sources and sizes, generating for defensible, valid, scalable, reproducible and documented machine learning and artificial intelligence models (predictive or optimization) for problem solving and strategy development. Participates in internal and external communities of practice in data science/artificial intelligence/machine learning to advance knowledge in the field. Educates the non-technical community on advantages, risks, and maturity levels of data science solutions.

Responsibilities:

• Supports the research and application of knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions
• Supports the creation of data mining architectures / models / protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets
• Extracts, transforms, and loads data from dissimilar sources from across PG&E for their machine learning feature engineering.
• Supports the application of data science/ machine learning//artificial intelligence methods to develop defensible and reproducible predictive or optimization models,
• Supports the development of mathematical models and AI simulations that represent complex business problems
• Writes and documents python code for data science (feature engineering and machine learning modeling) under senior data scientist guidance.
• Communicates technical information clearly to business.
• Contributes to the development of summary presentations
• Supports peer review exercises

Qualifications

Minimum Qualifications:

• Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
• 2 years in data science (or no experience, if possess Master’s Degree, as described above).

Desired Qualifications:

• Master’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
• Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience
• Familiarity with data science standards and processes (model evaluation, optimization, feature engineering, etc.) along with best practices to implement them).
• Knowledge of software engineering, statistics, and machine learning techniques as they apply to data science modeling and deployment.
• Knowledge of commonly used data science and/or operations research programming languages, packages, and tools
• Hands-on experience of data science/machine learning models and algorithms
• Ability to clearly communicate complex technical details and insights to colleagues and stakeholders.
• Knowledge of the mathematical and statistical fields that underpin data science
• Knowledgeable of best practices in software engineering, statistics, and machine learning techniques for data science.
• Knowledge of systems thinking and structuring complex problems
• Ability to collaborate and/or work on a team
• Previous experience working with utility data
• Previous experience with load forecasting
• Working knowledge power flow concepts and tools
• Live within 50 miles of headquarters