Product Engineer (Advance Data Analytics), Heterogeneous Integration Group (Hig), High Bandwidth Memory (Hbm) Product Engineering

Key Responsibilities Product Disposition Solutions: Develop, validate and deploy product-disposition solutions (wormhole) to ensure quality and reduce Defects Per Million (DPM) through a comprehensive product disposition program/workflow. Data Analysis for Yield Improvement and Reliability : Utilize in-house statistical tools, machine learning, and AI for engineering data analysis to enhance yields and reliability, integrating these improvements within the Dispo workflow. Deviation Alert System: Create a deviation alert system to monitor yield loss, characteristic/parameter trends, and wafer/die/cube shading. Models/Algorithm Development : Develop state-of-the-art algorithms, including Machine Learning and Deep Learning models, to advance data mining and pattern recognition for quality enhancement, yield improvement, wafer/die level screening and efficiency enhancement. Mentorship and Development: Actively mentor and develop team members to foster growth and development within the team and the organization. Cross-Functional Collaboration: Work closely with various cross-functional teams, including Fab, HBM Technology Development, HBM Design, System Development, and Quality/Reliability teams, to ensure the holistic development and successful shipping of end products. Promotion of Innovation: Promote innovation and drive changes that provide a technical advantage over competitors, maintaining the company's competitive edge in the market. AI/ML Advocate: Collaborate with cross-functional teams to develop, deploy, and validate AI/ML models aimed at enhancing key performance indicators (KPIs) such as Quality, Cost, Cycle Time, and Scale. AI Responsibilities: • Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements. • Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work. • Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business outcomes Requirements Bachelor's or Master's degree in Electrical and Electronics Engineering, Statistics, or related engineering fields. At least 3 years of experience in data analytics or data science is preferred. Prior experience in Micron Product Engineering or the semiconductor industry is a plus. Outstanding fresh graduates are welcome to apply. Demonstrate strong leadership and technical skills with a deep understanding of data analytics, data extraction, and analysis tools such as JMP, Tableau, and Power BI. Excellent communication skills to present findings and insights to non-technical stakeholders. Proven track record of collaborative work within/across teams to address sophisticated business and engineering problems. Experience in mentoring and coaching team members to develop their skills. Dedicated and highly motivated with a flexible approach towards adapting to different roles in a dynamic working environment (from leading the team to leading technical programs). Strong sense of responsibility and accountability towards assigned role with professional work ethic. Work on site in Singapore with international travel to Taiwan.