Manufacturing Data Analytics Engineering Intern

Lumentum • San Jose, CA

1d • $24 - $54 • Onsite

About The Position

Join the Manufacturing & Product Engineering team at Lumentum, where you will support yield improvement and process optimization for high-speed optical modules. This internship focuses on mining production line data, structuring it into JMP-compatible formats, and enabling engineers to perform statistical process control (SPC), Cp/Cpk analysis, and yield correlation studies. You will help transform raw manufacturing data into actionable insights that improve process capability, reduce variation, and enhance overall production yield. You will work closely with manufacturing, process, and product engineers to identify key drivers of yield loss and process instability across assembly and test operations.

Requirements

• Currently enrolled in a Bachelor’s or Master’s degree program in Industrial Engineering, Electrical Engineering, Mechanical Engineering, Data Science, or a related technical field.

Nice To Haves

• Experience with statistical analysis and process capability concepts (SPC, Cp, Cpk, GR&R).
• Proficiency in Python (Pandas, NumPy) or similar data analysis tools.
• Familiarity with JMP or other statistical process control software is strongly preferred.
• Exposure to manufacturing systems, MES databases, or SQL querying is a plus.
• Understanding of yield analysis and process variation reduction methodologies.
• Strong analytical thinking and ability to interpret large datasets.
• Effective communication skills and ability to collaborate with cross-functional teams.
• A proactive, hands-on mindset with interest in manufacturing process improvement.

Responsibilities

• Extract and mine large datasets from production line systems, MES databases, and test platforms.
• Clean, structure, and map manufacturing data into JMP-ready formats for advanced statistical analysis.
• Perform SPC analysis, including control chart development and process monitoring.
• Calculate and interpret Cp/Cpk metrics to evaluate process capability and identify variation sources.
• Correlate upstream process parameters with downstream module test results and yield performance.
• Support root cause analysis for yield excursions and process out-of-control events.
• Develop automated Python scripts to streamline recurring data preparation and reporting workflows.
• Partner with process and manufacturing engineers to recommend data-driven process improvements.
• Document findings and present yield improvement recommendations to engineering teams.

What This Job Offers

• Career Level: Intern