Resume

Worked as part of the intelligent manufacturing, a growing dedicated data science team within semiconductors:
1. Created data-driven solutions to semiconductor operations problems (e.g. defect detection, fail rate analysis) across various departments using machine learning and statistics. 
2. Used EDA, statistical tools, machine learning modelling algorithms, and model performance tools to create a back-end model to estimate the control wafer fail rate.
3. Developed AIOps for IT Operations, focusing on analyzing and prioritizing millions of events on K8S.
4. Researched and implemented computer vision-based defect detection and provided continual support for the product. 
6. Developed and deployed deep learning models for object detection.
6. Built statistical models to recognize risky situations using a combination of inline and offline monitors in Foundry.ai.
7. Improved existing models by resolving practical and algorithmic issues.
8. Developed scalable production Python code for client deployment.
9. Supported various Data Science projects.