Data Science Professional

Role Overview:

• Design and deploy machine learning models to solve critical business challenges within the semiconductor manufacturing sector.
• Create computer vision algorithms optimized for production environments, ensuring seamless integration with legacy systems.
• Partner with domain experts to define problem statements that align with organizational KPIs in chip design and quality control.

Key Responsibilities:

• Collaborate with data engineering teams to build robust pipelines for model training on large-scale datasets typical of semiconductor fabrication.
• Analyze massive data volumes from manufacturing processes (wafer inspection, yield analysis) to drive actionable insights and improve process control.
• Optimize ML models specifically tuned by PSMC's AI team for high-volume scalability and varying production conditions.

Technical Requirements:

• Demonstrated proficiency in Python with a deep understanding of CNN, RNN, and DNN mathematics applied to visual inspection tasks.
• Experience deploying computer vision models (object detection/segmentation) on Linux-based infrastructure common in fab environments.
• Ability to debug code efficiently while maintaining high standards for data integrity and quality validation processes essential in semiconductor operations.

Soft Skills:

• Strong communication skills to translate complex technical findings into clear visualizations for cross-functional manufacturing, IT, and leadership teams.
• Eagerness to learn emerging AI/ML tools specific to the electronics industry while fostering collaboration across global workforces.