Data Analytics Intern: Drift Detection for Semiconductors

Micron; Singapore; On-site; SGD 17,000 - 33,000; Full time

Job summary

Micron Singapore invites you to join a structured internship in data analytics to accelerate detection of cell metric drift using large-scale manufacturing data. You will work with experienced engineers to build detection models, dashboards, and technical reports from inline, probe, cell metric, and quality data.

The ideal candidate is pursuing a degree in Materials Science, Electrical & Electronic Engineering, Data Analytics, Statistics, or Computer Science, and can commit to a full-time

Qualifications

• Strong analytical, problem-solving, and data-interpretation skills.
• Experience with data analytics, statistical analysis, or visualization tools.
• Familiarity with Python, R, SQL, Power BI, or similar analytical tools is advantageous.
• Familiarity with AI-enabled data-analysis workflows is advantageous.

Responsibilities

• Develop data analytics and detection models for early identification of cell metric drift.
• Analyze relationships among inline, probe, cell metric, and quality data.
• Develop dashboards and visualizations to communicate analytical insights.
• Communicate findings through technical documentation and dashboards.
• Explore AI-enabled workflows for data exploration and productivity where relevant.

Skills

Analytical skills

Problem-solving

Data interpretation

Data analytics

Statistical analysis

Data visualization

Python

R

SQL

Power BI

AI workflows

Education

Materials Science

Electrical & Electronic Engineering

Data Analytics

Statistics

Computer Science

Tools

Python

R

SQL

Power BI

Job description

Micron Singapore invites you to join a structured internship in data analytics to accelerate detection of cell metric drift using large-scale manufacturing data. You will work with experienced engineers to build detection models, dashboards, and technical reports from inline, probe, cell metric, and quality data.

The ideal candidate is pursuing a degree in Materials Science, Electrical & Electronic Engineering, Data Analytics, Statistics, or Computer Science, and can commit to a full-time