SR. Data Scientist

Work with an international team of data scientists, data engineers, software engineers, process and equipment engineers, process integration engineers, yield enhancement engineers, and R&D in a collaborative manner to develop new data science solutions that improve quality, improve yield, reduce deviations, improve manufacturing cycle time, reduce cost, and extend manufacturing capabilities. Draw from a broad background of techniques in mathematics, statistics, information technology, machine learning, data engineering, and visualization to discover insightful patterns in data Work on projects and develop solutions of high impact in semiconductor manufacturing, taking (in collaboration with other teams) ownership of full pipeline from data-acquisition, through building and deploying machine learning models to visualization to user. Collaborate within an international team of data scientists, data engineers, software engineers, process and equipment engineers, process integration engineers, yield enhancement engineers, and R&D Explore and drive value from new data from new sensors or becoming available collaboration with suppliers or other business partners B.S./M.S. degree in Data Science, Computer Science, Industrial Engineering or other engineering discipline. PHD in related disciplines is a plus. At least 3 year experience in data science in engineering or related industry with in-depth knowledge in statistical modeling, machine learning, deep learning. Strong skills in python and at least familiar with 1 machine learning framework(like pyTorch, sklearn etc.). Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques. Experience working in Google cloud platform or other big data platform is a plus. Strong skills to quickly build prototype solutions based on business requirements, experience deploying data science solution into production environments. Excellent communication skills for explaining models, assumptions, and results to non-technical stakeholders, able to work independently with internal and external stakeholders to drive ideas to resolution. Proactive problem-solving approach and ownership mindset. Passion and interest to learn semiconductor manufacturing to deal with terabytes and petabytes of data to solve memory wafer related problems, enjoy working in diverse environment. Experience with Generative AI solutions including RAG, LLM tuning, agentic problem solving. Solid experience with RCA (root cause analysis) related algorithms and modeling in solving complex industry problems is a plus. Good full stack skills to build end-to-end data science application with scalability and robustness is preferred. Experience working with Manufacturing Execution Systems (MES), or good knowledge in wafer process and yield analysis is a plus Existing papers from CVPR, NIPS, ICML, KDD, and other key conferences are plus, but this is not a research position.