Data Science & Product Yield Analytics Engineer
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Role details
Tech stack
Job description
You will work closely with Data Scientists, Data Engineers, Product Engineers, Build teams, Yield Enhancement, RDA, Failure Analysis, and IT teams across global sites to develop and expand ESDA capabilities and analytics platforms that directly support manufacturing and product development., * Expand and enhance ESDA capabilities to improve yield, quality, and product reliability.
- Develop yield, defect matching, and modeling methods to accelerate manufacturing feedback to RDA and YE teams.
- Create and maintain engineering software tools for ESDA analytics and product line monitoring.
- Collaborate with design, failure analysis, and product teams to optimize redundancy, compression, and defect analysis methodologies.
- Support next-generation memory devices through advanced analytics and data-driven insights.
- Using AI in applicable job functions, Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.
AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate’s true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification.
Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.
Requirements
- BS or MS in Electrical Engineering, Computer Engineering, Data Science, Software Development, or a related technical field.
- Proficiency in at least one programming language and familiarity with machine learning and data science techniques.
- Familiarity with Microns Improved Software for Defect Analysis (ESDA) system, * Experience with memory products in product engineering, test, build, yield improvement, software development, or data science.
- Strong analytical and problem-solving skills applied to sophisticated manufacturing data.
- Ability to communicate complex technical concepts effectively across global, multi-functional teams.
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