Data Engineering Intern: Smart Manufacturing & Scheduling

Infineon Technologies AG; Singapore; On-site; SGD 13,000 - 18,000; Part time

Job summary

Infineon Technologies AG in Singapore invites an internship focused on applying AI-based optimization to manufacturing. You will analyze data quality, model performance, and correlation with scheduling efficiency, collaborating with a global team across production and supply chain.

You will gain hands-on experience in semiconductor manufacturing processes, data engineering, and data-driven analytics, culminating in a final technical presentation of outcomes.

Qualifications

• Pursuing or holding a Bachelor's/Master's degree in Industrial Engineering, Mathematics, or Computer Science.
• Experience in problem modeling and data engineering.
• Excellent communication and teamwork in a global setup.
• Strong analytical and problem-solving abilities.
• Internship duration from May 2027 to Dec 2027 (6 months or more).

Responsibilities

• Data & Model Analysis: analyze data quality vs model quality for scheduling.
• Troubleshooting Methodology: digitalize troubleshooting processes for model solutions.
• Documentation & Training: provide docs and training on digital tools.
• Stakeholder Collaboration: work with production, supply chain, and planning.
• Manufacturing Knowledge: understand semiconductor manufacturing and scheduling.
• Data & Model Relationship: study data quality to model performance links.
• Analytical Methods: apply data-driven methods to identify trends.
• Technical Presentation: deliver a final presentation with findings and recommendations.

Skills

Data analysis

Modeling

Data engineering

Communication

Teamwork

Analytical skills

Technical presentation

Stakeholder collaboration

Education

Bachelor's or Master's in Industrial Engineering

Mathematics

Computer Science

Job description

Infineon Technologies AG in Singapore invites an internship focused on applying AI-based optimization to manufacturing. You will analyze data quality, model performance, and correlation with scheduling efficiency, collaborating with a global team across production and supply chain.

You will gain hands-on experience in semiconductor manufacturing processes, data engineering, and data-driven analytics, culminating in a final technical presentation of outcomes.