PG&E's Applied Technology Services (ATS) team is looking for a Predictive Modeling Intern to join our team. You will help develop statistical models to evaluate and predict component failures and risk, gaining hands‑on experience with real-world datasets and advanced modeling techniques.
What You'll Do
- Assist in collecting, cleaning, and integrating datasets and help build simple data pipelines from internal sources to support analytics and operational insights.
- Support the development, testing, and maintenance of statistical or machine learning workflows by learning team tools and cloud platforms under guidance from senior engineers.
- Contribute to dashboards, reports, and data summaries that help communicate findings and support engineering and operational decision‑making.
What We're Looking For
- Currently pursuing a bachelor's, master’s, or PhD degree in Data Science, Electrical, Materials, or Mechanical Engineering, Statistics, or a related field.
- Must be continuing their education toward a degree during and/or after the internship.
Nice to Have
- Pursuing a PhD in Engineering, Statistics, Data Science, or a related field, with a power systems emphasis preferred.
- Proficient in Python.
- Strong foundation in statistics and/or machine learning.
- 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.
Technical Stack
- Python
- AWS
- Foundry
Team & Environment
You will join the Applied Technology Services (ATS) unit, a multidisciplinary team of over 120 engineers, scientists, and technicians.
Work Mode
This is an onsite internship located in Danville.
PG&E is an equal opportunity employer.
