Yield Analytics Engineer - Data-Driven Packaging

Intel; Albuquerque (NM); Hybrid; USD 122,440 - 232,190; Full time

Benefits offered by this job

Stock bonuses

Health insurance

Retirement plan

Paid time off

Job summary

Intel is seeking an experienced Yield Analysis engineer in the United States (Albuquerque, NM) to drive yield and defect improvements across the APTM packaging portfolio. The role involves analyzing large datasets, applying statistical methods, and collaborating with Process Engineering, QA, and Development teams to accelerate technology transfer and ramp to high-volume manufacturing.

The candidate should have a strong background in data analysis, inline metrology, and manufacturing processes,

Qualifications

• Bachelor's degree with 4+ years of relevant experience or Master's with 3+ years or PhD in a related discipline.
• 5+ years of experience in data analysis through JMP, Python, or other data engineering software.

Responsibilities

• Extract insights from structured and unstructured data by quickly synthesizing large volumes of data, applying statistical methods and machine learning techniques.
• Develop solutions to problems by utilizing formal education, knowledge of manufacturing process, statistical knowledge, and problem‑solving tools.
• Independently drive recommendations and influence the Yield improvement roadmap.
• Develop an understanding of FIFA, DFT, Sort/Test, Integration/Process Flow, Datamining, Databases, Data manipulation, and Data visualization.

Skills

Data analysis

Statistical knowledge

Problem solving

Education

Bachelor's degree +4 years

Master's degree +3 years

PhD in related field

Tools

Python

JMP

Job description

Intel is seeking an experienced Yield Analysis engineer in the United States (Albuquerque, NM) to drive yield and defect improvements across the APTM packaging portfolio. The role involves analyzing large datasets, applying statistical methods, and collaborating with Process Engineering, QA, and Development teams to accelerate technology transfer and ramp to high-volume manufacturing.

The candidate should have a strong background in data analysis, inline metrology, and manufacturing processes,