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Experienced
About the role
This role sits within the NAND Technology Department at a semiconductor company in Singapore, focused on yield analysis for memory technology development. It suits an experienced engineer who enjoys data analytics and asking what, how and why, and who can collaborate across many functions up to executive level.
What you'll do
Discover yield issues in NAND development and identify metrics or metric combinations, such as wafer, dice or tile shading, ECATS or other custom metrics, to quantify issues
Work with process area, process integration, yield, failure analysis, product engineering, design and layout teams to define yield, cell, CMOS, qual and reliability issues, pareto them and derive improvement actions across tech-nodes and designs
Own and drive non-standard deep dive statistical analysis of inline, probe, cell and other critical metrics to define problems, enable early inline detection and improve product yield and quality
Quantify and track progress on issue hit rate, line impact and gap to program goal, and quantify yield improvement or downside from process and probe changes
Initiate data mining and correlation studies on new issues, raise PFA requests to find root causes, perform inline correlation studies to establish inline prediction of yield issues, and make yield projections based on expected improvement or downside
Conduct yield trend analysis and identify root causes in process steps, conversion, algorithm changes and design for yield shifts
Continuously develop and redefine inline detection with the metrology and RDA team
Identify and define gaps in current test and co-develop unique parametric or probe bins with product, probe and param engineering to detect new fail modes and validate new program releases
Collaborate with module owners to identify and quantify key module deficiencies and technology gaps, and drive cross-functional teams to address them; optimise existing layout and conceptualise innovative solutions to meet product requirements and manufacturability
Develop and innovate techniques to extract data from different databases using various query languages and automate through scripting to improve work efficiency
Support the transfer documentation of layout and architecture fundamentals of new technology from R&D to the manufacturing fab
Integrate AI-assisted tools and insights into daily work to improve efficiency, quality or effectiveness, exercising sound judgment and complying with organisational standards and legal requirements
Contribute to a culture of continuous improvement by identifying, testing and sharing AI-enabled enhancements within your scope of work
Good to know
Location: Fab 10N/X, Singapore
Full time position
Requirements
Bachelor's degree or Master's in Electrical and Electronics Engineering or Material Science
5 to 7 years of experience in failure analysis, yield analysis or yield enhancement
Ability to discover yield issues in NAND development and identify metrics or metric combinations such as wafer, dice or tile shading, ECATS or other custom metrics for issue quantification
Deep understanding of probe failure mechanisms
Ability to perform electrical bench data collection is desirable
Fluency in Python, JavaScript, C or C++
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