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 (e.g., Foundry, AWS) under guidance from senior engineers.
Contribute to dashboards, reports, and data summaries that help communicate findings and support engineering and operational decision‑making.

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
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.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Pythonstatisticsmachine learningdata pipelines

Soft Skills

problem solvingenthusiasm for learningcommunication