Data Scientist

Build and deploy machine learning and AI models to support predictive and optimization problem-solving across PG&E.

Responsibilities

• Apply existing and emerging data science principles, theories, and techniques to inform business decisions
• Support creation of data mining architectures, models, protocols, statistical reporting, and data analysis methodologies to surface trends in structured and unstructured datasets
• Extract, transform, and load data from disparate PG&E sources for machine learning feature engineering
• Use data science, machine learning, and artificial intelligence methods to develop defensible, reproducible predictive or optimization models
• Develop mathematical models and AI simulations that represent complex business problems
• Write and document Python code for data science (feature engineering and machine learning modeling) under senior data scientist guidance
• Communicate technical information clearly to business stakeholders
• Contribute to summary presentations
• Support peer review exercises

Requirements

• Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field
• 2 years of data science experience (or no experience if you possess a Master’s Degree in a listed field)
• Master’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field
• Relevant industry experience (electric or gas utility, renewable energy, analytics consulting, etc.)
• Familiarity with data science standards and processes, including model evaluation, optimization, and feature engineering, plus best practices
• 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 with data science or machine learning models and algorithms
• Ability to clearly communicate complex technical details and insights to colleagues and stakeholders
• Knowledge of the mathematical and statistical foundations of data science
• Knowledgeable of best practices in software engineering, statistics, and machine learning for data science
• Systems thinking and ability to structure complex problems
• Ability to collaborate and/or work on a team
• Previous experience working with utility data
• Previous experience with load forecasting
• Working knowledge of power flow concepts and tools
• Live within 50 miles of headquarters

Technology

• Python
• Machine learning
• Artificial intelligence
• Data science
• Operations research

Position Summary

• Design, develop, and execute scripts, programs, models, algorithms, and processes using structured and unstructured data from disparate sources
• Generate defensible, valid, scalable, reproducible, and documented machine learning and AI models for predictive or optimization problem solving and strategy development
• Participate in internal and external communities of practice in data science, artificial intelligence, and machine learning
• Educate non-technical community members on advantages, risks, and maturity levels of data science solutions

Team / Department Overview

• Electric T&D includes over 6,500 coworkers supporting clean, safe, reliable, and affordable energy for nearly 16 million people in Northern and Central California
• Electric T&D maintains and operates 100,000 miles of distribution lines and over 18,000 miles of Transmission lines to ensure grid reliability and resiliency
• Electric T&D uses Lean Methodology with Visual Management in Operating Reviews to cross-functionally identify and solve problems and create standard work
• Headquartered in Oakland, CA; hybrid role with expectation of in-office work 1x/week (subject to change)
• Within the Transmission Tools and Modeling (TTM) team
• TTM develops analytical tools, data solutions, and power system models for transmission planning and operational decision-making
• Team combines 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
• Works with planners, engineers, operations, and business partners to improve study efficiency, data quality, and modeling accuracy
• Focus on modernizing workflows, leveraging advanced analytics, and building scalable tools to turn complex grid data into actionable insights

Job Details

• Location: Oakland, CA (hybrid)
• Job Category: Accounting / Finance
• Job Level: Individual Contributor
• Business Unit: Strategy & Growth
• Work Type: Hybrid

Salary

• Bay Area: $102,000 - $162,000
• California: $97,000 - $154,000

Education: Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering (as specified in requirements).