Data Scientist Intern - System Performance Monitoring
About The Position
The System Performance, Reliability, and Resiliency Strategy team—part of the Electric Transmission & Distribution Engineering organization—supports PG&E’s mission to deliver safe, reliable, and resilient electric service. The team leads the planning, execution, and continuous improvement of the company’s Electric Reliability Strategy. This includes deploying advanced technologies, modernizing grid infrastructure, and supporting cross‑functional efforts to transition innovative projects from development and testing into full operational use. We are seeking a Data Scientist Intern to help develop and deploy system performance monitoring tools using operational datasets from the electric grid. In this role, you will collaborate closely with the System Performance Monitoring team at the intersection of data science, power engineering, data engineering, and large-scale data analysis. This internship offers hands‑on experience with real-world datasets, advanced modeling techniques, and emerging grid modernization technologies.
Requirements
- Currently pursuing bachelor's, master’s or PhD degree in Data Science, Electrical, Industrial, Mechanical, or Civil/Structural engineering, Statistics, or other related field
- Must be continuing their education toward a degree during and/or after the internship
Nice To Haves
- Pursuing a Ph.D. in Engineering, Statistics, Data Science, or a related field (power systems emphasis preferred)
- Minimum 3.0 GPA (cumulative and major)
- Proficient in Python
- Strong foundation in statistics and/or machine learning
- Understanding of power systems fundamentals such as power flows, per-unit analysis, symmetric components, and/or protection engineering
- Passion for solving complex technical challenges to support communities
- Enthusiasm for learning and adopting new tools, platforms, and technologies
- Excellent written and verbal communication skills
Responsibilities
- Data Management and Analysis: Assist in collecting, cleaning, and integrating datasets and help build simple data pipelines from internal sources to support analytics and operational insights.
- Model Development: Support the development, testing, and maintenance of statistical or machine learning workflows by learning team tools and cloud platforms (e.g., Foundry, AWS) under guidance from senior engineers.
- Visualization and Reporting: Contribute to dashboards, reports, and data summaries that help communicate findings and support engineering and operational decision‑making.
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What This Job Offers
Career Level
Intern
Education Level
No Education Listed
