Engineering Intern (Diablo Canyon Power Plant)

Pacific Gas And Electric Company
10d$23 - $36Onsite

About The Position

We are looking for a data science intern to join our team to help develop and deploy reliability analytics & predictive models to identify incipient failures on the electric grid. In this role you will work as a part of the Predictive Analytics team and System Performance Monitoring team to help improve the development of predictive and anomaly detection models. This is a role at the intersection of data science, engineering, data engineering, and data analysis. PG&E is providing the hourly rate 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 hourly rate 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.

Requirements

  • Pursuing master’s degree in Power System, Industrial, Mechanical, Structural engineering, Statistics, Data Science, or other related field
  • Students must be continuing their education towards their degree during and/or after the internship
  • PG&E is unable to provide VISA sponsorship to students on an F-1, J-1 or other student visa for this position.

Nice To Haves

  • Working toward a PhD degree in Power Systems, Industrial, Mechanical, Structural Engineering, Statistics, Data Science, or a related field
  • Minimum 3.0 GPA (both cumulative and major GPA)
  • Proficient in Python
  • Strong foundation in statistics and machine learning
  • Passion for solving complex problems to support communities and enthusiasm for learning new technologies
  • Excellent written and verbal communication skills

Responsibilities

  • Data Management and Analysis: Collecting, cleaning, integrating, and analyzing data from diverse internal and external sources.
  • Model Development: Designing, developing, and deploying analytical models (statistics and ML) and data pipelines across big data cloud platforms such as Palantir Foundry, Amazon AWS, and similar environments
  • Visualization and Reporting: Building interactive dashboards to visualize model performance, data analytics and communicate key insights.
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