Data Scientist, Semiconductor Manufacturing Analytics

What you'll do

• Analyze manufacturing, equipment, and metrology data to identify trends, anomalies, and root causes of process variation.
• Develop and validate machine learning models for yield prediction, excursion detection, and tool health monitoring.
• Build proof-of-concepts to demonstrate the feasibility of predictive analytics for Thermal Compression Bonding applications.
• Translate complex manufacturing problems into scalable data solutions in collaboration with engineering teams.
• Support advanced process control initiatives to improve manufacturing performance and stability.
• Create dashboards, reports, and automated tools to accelerate decision-making and response times in production environments.
• Ensure high standards of data quality and model validity for all manufacturing-related analytics.

What we're looking for

• Bachelor's degree with 6+ years of experience, Master's with 4+ years, or PhD with 2+ years in a relevant technical field.
• At least 2 years of experience in manufacturing data analysis and applying statistical methods to solve process or yield problems.
• Proficiency in Python programming and JMP for data analysis, automation, and model development.
• Experience working with large datasets from manufacturing, equipment, metrology, or quality systems.
• Ability to apply AI/ML, statistical methods, or predictive modeling to extract actionable insights for business decisions.
• Proficiency with SQL or other database query tools for data extraction and analysis.
• Experience in semiconductor manufacturing, preferably in assembly or advanced packaging (preferred).
• Understanding of advanced process control, yield analysis, and root cause investigation in a manufacturing environment (preferred).