Data Engineering Intern - ML Pipelines & Cloud

Itron; Liberty Lake (WA); On-site; USD 22,000 - 61,000; Full time

Benefits offered by this job

Hybrid work schedule

401k matching

Employee stock purchase program

Job summary

Itron is seeking a motivated 2027 Summer Data Science Intern to help advance innovation in the Utilities & Energy sector. You will work with experienced data scientists, software engineers, and stakeholders to support grid optimization, DER integration, and customer engagement.

This 10-week, 40-hours-per-week internship is based in Liberty Lake, Washington. You will develop, test, and maintain data pipelines, contribute to ML model improvements, and collaborate with cross-functional teams to

Qualifications

• Currently pursuing a relevant bachelor's degree with at least two years of coursework completed by start date.
• Experience with AI agent-driven tools to support software development, testing, or code review is required.
• Intermediate Python and SQL proficiency, plus knowledge of statistics and data analysis.

Responsibilities

• Support data and ML pipelines in production environments.
• Assist with cloud infrastructure implementation and maintenance.
• Clean, prepare, and validate large datasets for analysis and model development.
• Collaborate with data scientists, software engineers, and product managers to deliver solutions.

Skills

Python

SQL

AI agent tools

Data analysis

Statistical methods

Communication

Team collaboration

Education

Bachelor's in Statistics/Data Science/Applied Mathematics/CS/SE

Enrollment: 2+ years completed

Tools

AWS

Azure

GitHub

Job description

Itron is seeking a motivated 2027 Summer Data Science Intern to help advance innovation in the Utilities & Energy sector. You will work with experienced data scientists, software engineers, and stakeholders to support grid optimization, DER integration, and customer engagement.

This 10-week, 40-hours-per-week internship is based in Liberty Lake, Washington. You will develop, test, and maintain data pipelines, contribute to ML model improvements, and collaborate with cross-functional teams to