Senior Product Analytics Engineer
Tasks
- Analyze NAND reliability and defectivity using advanced analytics
- Build end to end machine learning workflows for NPI and HVM decisions
- Collaborate with fab and engineering teams on reliability and defectivity failures
- Create structured learning paths and training modules for machine learning
- Design and implement agentic AI automation for product engineering workflows
- Develop predictive and diagnostic machine learning models for yield improvement
- Integrate AI agents with JIRA Confluence SharePoint and internal analytics platforms
- Mentor citizen data scientists and review AI projects
- Optimize cost using machine learning workflows
- Perform root cause analysis for yield reliability and defectivity issues
- Reduce test time using data driven analysis
- Support yield improvement cost reduction and test optimization initiatives
Perks/Benefits
- N/A
Skills/Tech-stack
AWS SageMaker | Agentic AI | Azure Machine Learning | Cause analysis | Copilot Studio | Data Processing | Decision Trees | Deep learning | Gradient boosting | Langchain | Language Models | Language Processing | Large Language Models | Machine Learning | Microsoft Copilot | Microsoft Copilot Studio | Natural Language | Natural Language Processing | NumPy | Pandas | PyTorch | Python | Regression | Root Cause Analysis | Root cause | Scikit-learn | TensorFlow
Education
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