Staff Yield Engineer Data Analytics

ADVANCED MICRO DEVICES (SINGAPORE) PTE LTD; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

A leading semiconductor company in Singapore is looking for an experienced professional to support the development and launch of high-quality AI and graphics products. Responsibilities include optimizing manufacturing costs, engaging in cross-functional collaboration, and analyzing yield metrics. The ideal candidate should have at least 7 years of experience in product development with semiconductor technologies, strong data analysis skills, and the ability to work in diverse teams. A Bachelor's degree in a relevant field is also required.

Qualifications

• 7+ years of experience in process technology or product development.
• Experience with leading-edge foundries, assembly, and test operations.
• An advanced degree may reduce the minimum experience requirement.

Responsibilities

• Support development and launch of AI, Graphics, and custom design products.
• Optimize manufacturing costs and ensure market delivery.
• Engage with teams to define program requirements for quality and yield targets.
• Collaborate with internal and external teams for process improvements.

Skills

Data analysis and yield engineering

Experience with data analysis tools (JMP or equivalent)

Database querying and SQL

Strong AI-forward data science skills

Strong scripting capability

Understanding of functional and design-for-test methodologies

Technical expertise in productization

Knowledge of semiconductor device physics

Semiconductor manufacturing experience

Ability to work in diverse teams

Education

Bachelor's Degree in Electrical Engineering, Computer Engineering, or Computer Science

Tools

JMP

Job description

THE ROLE

You will be supporting the development and launch of high-quality AI, Graphics, CPU, APU, and custom design products in the Product Yield Engineering team. You will optimize manufacturing costs and ensure timely market delivery. You will be involved in cross‑functional collaboration with engineering, design, foundry, and data teams to resolve complex challenges, accelerate product ramp‑up, and drive ongoing yield improvements.

KEY RESPONSIBILITIES

• Data analysis and yield engineering, focusing on post‑testing data, presentation, and understanding fabrication/testing processes
• Analyzing data across various products
• Manage product wafer costs, including yield and test content, to meet quality and yield targets
• Analyze yield metrics to forecast supply and product performance
• Implement best practices for test and characterization
• Use diagnostics and failure analysis to reduce defects in foundry environments
• Collaborate with internal and external foundry teams to identify and implement process improvements
• Engage with engineering, product teams and business units to define and achieve program requirements for defectivity, power, performance, reliability, and quality

PREFERRED EXPERIENCE

The ideal candidate will have the following minimum skills:

• Minimum 7 years of experience in process technology or product development, preferably with leading‑edge foundries, assembly, and test operations.
• Direct experience in JMP or equivalent data analysis tools.
• Database querying and SQL
• An advanced degree in a related field may reduce the minimum experience requirement

In addition, we value these technical competencies in our team:

• Strong AI‑forward data science skills with experience in big data models, databases, and machine learning
• Strong scripting capability including using AI to extract and automate complex data analysis
• Understanding of functional and design‑for‑test methodologies, structures, and practices
• Technical expertise in the productization of new and advanced technologies
• Knowledge of leading edge (FinFET, GAA, etc.) semiconductor device physics
• Semiconductor manufacturing experience
• Ability to work effectively in geographically distributed and diverse teams

ACADEMIC CREDENTIALS

• Bachelor's Degree in Electrical Engineering, Computer Engineering, or Computer Science, or a related degree in Math, Sciences, or Statistics.