Reliability Data Analytics Intern (AI/ML)

Sacramento Municipal Utility District

Sacramento (CA)

On-site

USD 51,000 - 62,000

Full time

3 days ago
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Job summary

Sacramento Municipal Utility District (SMUD) seeks a Reliability Compliance Intern to support RC&C with data analysis, risk assessment, and AI/ML initiatives in a student internship role. You will work across technical and business teams to validate data, support program requirements, and explore automation opportunities while learning SMUD's risk frameworks and compliance standards.

The internship emphasizes hands-on experience in reliability risk management, AI/machine learning, and

Qualifications

  • Must be a full‑time student (12+ units) in STEM.
  • Majors in Risk Management, STEM fields, or related areas.
  • Experience with Power BI and Excel/PowerPoint is preferred.
  • Strong analytical skills and data computations.
  • Ability to develop code and communicate clearly.

Responsibilities

  • Collect, organize, clean, validate, and analyze data for reliability risk and compliance.
  • Refine data, validate risk information, and perform data quality reviews.
  • Identify opportunities to apply AI/ML to improve processes.
  • Develop, test, and maintain scripts for data processing.
  • Support design, training, and evaluation of AI/ML models.
  • Prepare documentation, presentations, and reports.

Skills

Analytical skills
Communication
Coding ability
Team collaboration
Eagerness to learn

Education

STEM student enrolled 12+ units

Tools

Power BI
Excel
PowerPoint
Microsoft Office Suite

Job description

Sacramento Municipal Utility District (SMUD) seeks a Reliability Compliance Intern to support RC&C with data analysis, risk assessment, and AI/ML initiatives in a student internship role. You will work across technical and business teams to validate data, support program requirements, and explore automation opportunities while learning SMUD's risk frameworks and compliance standards.

The internship emphasizes hands-on experience in reliability risk management, AI/machine learning, and

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