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Advanced Data Scientist
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Unlock the Power of Advanced Data Analytics
Join a visionary team as Principal Product Engineer and spearhead initiatives that significantly enhance yield and quality through cutting-edge data analysis, machine learning, and AI.
Key Responsibilities:- Cumulative Yield Ownership: Lead cross-functional teams to drive impactful initiatives for overall yield and quality improvement, delivering substantial benefits to the organization.
- 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.
- 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.
- 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.
- Deviation Alert System: Create a deviation alert system to monitor yield loss, characteristic/parameter trends, and wafer/die/cube shading.
- Data Infrastructure Development: Collaborate with IT, Manufacturing, and Operations teams to develop and enhance the data infrastructure pipeline using cloud technologies to support reliability and engineering assessments.
- 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 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.
- Bachelor's or Master's degree in Engineering, Computer Science, Statistics, Artificial Intelligence, or related fields.
- At least 10 years of experience in data analytics/science industry. Experience in Micron Product Engineering or the semiconductor industry is preferred.
- Proven experience in leading analytic projects from conception to completion.
- 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.
- Highly proficient in statistical analysis, predictive modeling, and machine learning techniques, including extensive experience with libraries such as TensorFlow, Scikit-learn, and PyTorch.
- Proficiency in programming languages such as Python, R, SQL, and web application languages like JavaScript, HTML, and CSS for advanced data manipulation and analysis.
- 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.
- 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).
- Experience in mentoring and coaching team members to develop their skills and advance their careers.
- Strong sense of responsibility and accountability towards assigned role with professional work ethic.
- Work on site in Singapore with international travel to Taiwan.
