Data Scientist at C0000161245P

Department: CCA Regulatory ProceedingsSeniority in posting: Individual Contributor

Language

Compensation

$102,000 – $162,000/yr

Setup: Hybrid
Location: Hitachiomiya, Ibaraki Prefecture
Type: Full-time
Level: mid
Posted: Sep 23, 2026

Summary from listing

PG&E is hiring a Data Scientist for its Cost-of-Service team to support electric and gas rate design proposals in regulatory proceedings. The role develops and executes data mining, statistical, machine learning, optimization, and AI models; engineers features; writes Python; documents and reviews models; presents insights; and collaborates cross-functionally. The position is hybrid, with remote work and Oakland General Office attendance once per week, and offers a Bay Area salary range of $102,000 to $162,000 plus discretionary incentive compensation.

Required Skills

Data science
Machine learning
Python
Feature engineering
Optimization
Statistics
Data mining

Additional Information

Minimum Education: Bachelor’s degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or an equivalent field
Required Previous Experiences: 2 years of data science experience, or no experience if the candidate holds a master’s degree
Preferred Qualifications: Relevant industry experience in electric or gas utilities, renewable energy, or analytics consulting
Knowledge of finance and economics applied to utility rate design
Knowledge of data science standards, processes, model evaluation, optimization, and feature engineering
Competency in software engineering, statistics, and machine learning for data science deployment
Competency with commonly used data science and operations research programming languages, packages, and tools
Hands-on and theoretical experience with data science and machine learning models and algorithms
Ability to synthesize complex information into clear insights and translate them into decisions and actions
Competency in the mathematical and statistical fields underlying data science
Mastery of systems thinking and structuring complex problems
Ability to develop, coach, and teach career-level data scientists in data science, artificial intelligence, and machine learning