Senior Yield & Process Analytics Engineer — On-Site

Bzpp; United States; Vor Ort; USD 95.000 - 120.000; Vollzeit

Benefits dieser Stelle

Medical, dental, and vision insurance

Life insurance and 401(k) matching

Onsite cafés and gyms

Paid maternity and paternity leave

Paid time off and holidays

Wellness incentives

Zusammenfassung

Samsung Austin Semiconductor seeks a highly analytical Yield and PCI Engineer to monitor wafer manufacturing, drive yield improvements, and investigate process excursions. You will use SPC, defect data, and parametric results to identify root causes and implement stable, high-yield processes with cross-functional teams.

The role emphasizes data-driven modeling, advanced analytics in Python/JMP/SQL, and leadership in yield management across multiple technology nodes.

Qualifikationen

• Bachelor’s or Master’s degree in a related engineering field.
• Strong understanding of semiconductor device physics and CMOS processes.
• Experience with data analytics, SPC, and failure analysis methods.

Aufgaben

• Predictive yield modeling using inline metrology and defect data.
• Baseline yield forecasting for ramp and mature nodes.
• Yield analysis across wafer sort, parametric, and final tests to identify limiters.
• Lead root-cause analysis and collaborate with Design and Product teams.
• Apply data science techniques to build yield models and analytics pipelines.
• Define roadmaps, KPIs, and lead-Yield management initiatives.

Kenntnisse

Analytical problem solving

Technical writing & presentation

Cross-functional leadership & comms

Ausbildung

B.E./M.Sc. in Electrical Eng, Materials Science, Physics, Applied Physics

Tools

Python

JMP

SQL

Jobbeschreibung

Samsung Austin Semiconductor seeks a highly analytical Yield and PCI Engineer to monitor wafer manufacturing, drive yield improvements, and investigate process excursions. You will use SPC, defect data, and parametric results to identify root causes and implement stable, high-yield processes with cross-functional teams.

The role emphasizes data-driven modeling, advanced analytics in Python/JMP/SQL, and leadership in yield management across multiple technology nodes.