Product Engineering Analyst (Yield & Data)

Overview

Drive data‑driven insights across semiconductor test structures and product lifecycles. Strong focus on yield improvement, failure analysis and product performance. Transform large‑scale manufacturing and test data into actionable insights. Collaborate at the intersection of Yield Engineering, Product Engineering and Data Science. Improve yield, quality and cost through advanced analytics and automation. Apply strong semiconductor domain expertise combined with data analysis capabilities.

Must Have

• Strong experience in data analysis within semiconductor or manufacturing environments
• Proficiency in Python (Pandas, NumPy, SciPy, Matplotlib)
• Strong knowledge of statistics and data modeling
• Understanding of semiconductor yield concepts and test flows (CP/FT)

Responsibilities

• Analyze large‑scale datasets from wafer sort (CP), final test (FT) and fab processes to drive yield and product insights.
• Conduct Pareto analyses, binning studies and correlation analyses across process, test and product parameters.
• Identify systematic yield limiters and lead root‑cause investigations of product and process failures.
• Develop and apply statistical and data‑driven models to support yield and performance optimization.
• Design, develop and maintain automated data pipelines and analysis tools.
• Create dashboards, automated reports and visualization tools for scalable insights.
• Enable data‑driven decision‑making across cross‑functional teams and stakeholders.

Your profile

• Basic programming proficiency, particularly in Python.
• Experience with SQL and database querying.
• Strong analytical mindset with a high level of attention to detail.
• Ability to translate complex data into meaningful engineering insights and actionable recommendations.
• Proactive, automation‑driven approach to problem solving.
• Comfortable working in cross‑functional, collaborative environments.

Ideal fit

• Background in Electrical Engineering or Microelectronics.
• Expertise as a Product Engineer and/or Yield Engineer.
• Familiarity with semiconductor test data formats (STDF/ATDF), including wafer maps and binning analysis.
• Experience using data visualization and analytics tools to interpret large datasets.
• Working knowledge of Design of Experiments (DOE) and Statistical Process Control (SPC) methodologies
• Proficiency working with large‑scale data pipelines and/or cloud‑based data platforms.