NMSi Silicon Photonics Yield Analysis Engineer

Intel•Rio Rancho, NM

1d•Onsite

About The Position

As a Yield Analysis Engineer, you will analyze semiconductor manufacturing data to identify yield trends, investigate performance issues, and drive improvements in manufacturing processes. You will work with cross-functional teams to develop data-driven solutions that improve yield, reduce defects, and enhance product quality and reliability, supporting Intel’s next-generation silicon photonics technologies. The position is part of Intel’s manufacturing operations team, which supports the development and production of advanced semiconductor technologies. The team focuses on improving manufacturing yield, process efficiency, and product quality through data analysis, technical problem-solving, and cross-functional collaboration.

Requirements

Bachelor’s degree in a relevant field and 4+ years of experience in semiconductor manufacturing, data analysis, or a related field; or a master’s degree in a relevant field and 3+ years of experience; or a PhD in a relevant field with no prior professional experience required.
2+ years of hands-on experience using data analysis or programming tools such as Python, R, MATLAB, JMP, or equivalent.
2+ years of experience applying statistical methods and process control systems.
2+ years of experience working with large datasets and database management systems.

Nice To Haves

Strong communication and problem-solving skills, with the ability to work collaboratively across teams.
Familiarity with semiconductor manufacturing processes and materials.
Hands-on experience in yield analysis techniques and methodologies.
Ability to manage multiple projects in a fast-paced, dynamic environment.
Experience in semiconductor manufacturing and/or advanced packaging technologies.

Responsibilities

Analyze semiconductor manufacturing yield data to identify trends, anomalies, and opportunities for improvement.
Investigate yield issues and process deviations with cross-functional teams, identify root causes, and implement corrective actions.
Apply statistical methods and analytical tools to evaluate manufacturing performance and support data-driven decision-making.
Develop and implement strategies to improve yield performance, minimize defects, and optimize manufacturing processes.
Generate reports, analyze performance metrics, and provide actionable recommendations to improve product quality and reliability.
Support continuous improvement initiatives to achieve manufacturing yield targets and operational objectives.