Your role
Key responsibilities in your new role
- AI & Digitalization Projects: Work on digitalization or AI projects to improve productivity in manufacturing.
- Machine Learning Implementation: Work on various machine learning techniques and software to operationalize the solution.
- Stakeholder Engagement: Work with various technical experts in understanding the business requirement.
- Technical Exposure: Be exposed to different software systems and scripting languages to complete the project.
- Manufacturing Domain Learning: Be coached to understand Backend manufacturing processes and operations.
Internship Learning Outcomes:
- Semiconductor Industry Knowledge: Obtain an in-depth understanding of the semiconductor industry, Product Test Engineering, and Back-end testing.
- Data Analysis & Root Cause Investigation: Be exposed to various data analysis, statistics, and data engineering techniques and how they are used to identify root causes.
- Programming & Data Engineering Skills: Gain hands-on experience related to programming, data preparation, internal systems, and data architecture.
- Tools & Technology Proficiency: Gain real-life experience using in-house data extraction tools, data visualization tools, Python, Database Management, and ML tools.
- AI/ML Application Experience: Develop practical understanding of how AI and machine learning models are built, tested, and deployed in a manufacturing context.
- Cross-Functional Collaboration: Build experience working alongside technical experts and domain specialists to translate business requirements into data-driven solutions.
Your profile
Qualifications and skills to help you succeed
- Educational Background: On track to attain a Bachelor's or Master's degree in Data Science, Computer Science, Applied Mathematics, Statistics, Business Analytics, or a related technical discipline.
- Data & Programming Skills: Proficient in data mining, data visualization, and coding skills in Python.
- AI/ML Expertise: Experience in AI/ML/DL, Computer Vision (CV), and optimisation techniques.
- Self-Motivation & Learning Agility: Passion for AI and a high degree of self-initiative and independent learning.
- Communication & Analytical Skills: Strong communication and analytical skills to effectively engage with technical and non-technical stakeholders.
- Preferred intake: Jan 2027 - May 2027