AI-Powered Sustainability Intern: Data Dashboards & Analytics

Micron

Singapore

On-site

SGD 20,000 - 27,000

Full time

3 days ago
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Job summary

Micron Singapore offers an internship on an AI-powered Sustainability Command Center project. You will develop a structured data model, ingest and transform utility datasets, and build a Power BI dashboard for sustainability performance monitoring under experienced guidance.

The role emphasizes AI-assisted analytics, anomaly detection, and automated reporting, with collaboration across engineering, facilities, and sustainability teams. Five-month program Jan–May 2027.

Qualifications

  • Familiarity with data analytics, data modelling, data visualization, or reporting automation.
  • 0
  • Experience with Power BI, Excel, Python, SQL, Power Platform, or similar tools is advantageous.
  • Familiarity with AI concepts and AI-enabled analytics.
  • Strong analytical and stakeholder-engagement skills.
  • Interest in energy management, water management, carbon accounting, facilities utilities, or environmental sustainability.

Responsibilities

  • Develop a structured data model and repeatable data-processing workflow for selected data.
  • Build an interactive Power BI dashboard covering sustainability indicators, trends, and exceptions.
  • Apply rule-based or AI-enabled analytics for anomaly detection and insight generation.
  • Create an opportunity tracker and automate selected reporting outputs.
  • Prepare technical documentation, user instructions, and maintenance guidance.

Skills

Power BI
Microsoft Excel
Python
SQL
Power Platform
AI/Generative AI familiarity
Analytical skills
Stakeholder engagement

Education

Engineering/Data Science degree

Job description

Micron Singapore offers an internship on an AI-powered Sustainability Command Center project. You will develop a structured data model, ingest and transform utility datasets, and build a Power BI dashboard for sustainability performance monitoring under experienced guidance.

The role emphasizes AI-assisted analytics, anomaly detection, and automated reporting, with collaboration across engineering, facilities, and sustainability teams. Five-month program Jan–May 2027.

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