Wla Yield Defect Metrology Engineer

Intel Intel · Semiconductors · Oregon, Hillsboro, United States

Engineer focused on identifying root cause yield limiters in semiconductor manufacturing through statistical analysis, big data consolidation, and machine learning techniques. Develops methods and tools for high-volume data analysis to drive yield improvement actions and ensure manufacturability.

What you'd actually do

  1. Provides process development direction throughout the whole lifecycle of a technology node by identifying root cause yield limiters.
  2. Performs statistical analysis, develops visualizations and presentations to construct accurate process development roadmaps that drive technology yield milestones.
  3. Develops methods, processes, and systems to consolidate and analyze diverse big data sources, establishing optimal methodologies for defect mode understanding and yield modeling, leading to accurate yield Pareto construction and process roadmap definition.
  4. Organizes, interprets, and structures insights from fab process, defect, and electrical data and detects data anomalies and drives process changes for yield enhancement.
  5. Extracts insights from structured and unstructured data by quickly synthesizing large volumes of data, and applying statistics, machine learning and coding techniques.

Skills

Required

  • Metrology experience
  • Statistical and analytical techniques to yield or process improvement experience
  • Experience with analytical tools such as JMP, JSL, SQL/SQL Pathfinder
  • Bachelor's degree in Materials Science and Engineering, Mechanical Engineering, Computer Information Systems, Computer Science, Information Systems, Chemical Engineering, Electrical Engineering, Chemistry, Physics, or another STEM-related field, with 1+ years of relevant experience; OR Master's degree in the above fields with 6+ months of experience.

Nice to have

  • Python for data analysis and process modeling
  • Detailed knowledge of substrate, assembly, and fab back-end processes
  • Sense of ownership and collaboration with cross-functional partners to drive yield enhancement
  • Prior experience in defect reduction, yield analysis, or module engineering roles

What the JD emphasized

  • identifying root cause yield limiters
  • yield modeling
  • machine learning
  • data analysis