AI-Driven Sustainability Intern: Data & Dashboards

1100 Micron SemiAsiaOP Pte Ltd; Singapore; On-site; SGD 17,000 - 21,000; Full time

Job summary

Micron Technology, Inc. in Singapore invites applications for a full-time five-month internship to build an AI-powered Sustainability Command Center. You will consolidate energy, water, and cost data into a structured model, and develop a Power BI dashboard for operational visibility.

You will explore AI-assisted analytics, anomaly detection, and automation, with guidance from engineering and digital professionals. Apply for a meaningful engineering analytics experience.

Qualifications

• Pursuing a university degree in a relevant engineering or analytics discipline.
• Familiarity with data analytics, data modelling, and data visualization.
• Experience with Power BI, Excel, Python, SQL, or Power Platform is advantageous.
• Strong analytical and stakeholder-engagement skills.
• Interest in energy, water, carbon, or sustainability.

Responsibilities

• Consolidate data sources into a structured sustainability data model.
• Develop an interactive Power BI dashboard for indicators and trends.
• Apply AI-enabled analytics or anomaly detection methods.
• Prepare technical documentation and solution architecture.
• Collaborate with engineering, facilities, environmental, and sustainability stakeholders.

Skills

Data analytics

Data modelling

Data visualization

Reporting automation

Power BI

Excel

Python

SQL

AI familiarity

Stakeholder engagement

Communication

Education

Engineering degree (Mechanical/Electrical)

Data Science degree

Sustainability-related degree

Tools

Power BI

Microsoft Excel

Python

SQL

Power Platform

Job description

Micron Technology, Inc. in Singapore invites applications for a full-time five-month internship to build an AI-powered Sustainability Command Center. You will consolidate energy, water, and cost data into a structured model, and develop a Power BI dashboard for operational visibility.

You will explore AI-assisted analytics, anomaly detection, and automation, with guidance from engineering and digital professionals. Apply for a meaningful engineering analytics experience.