Opis
Key
Responsibilities
Yield & Process Optimization: Collaborate with semiconductor manufacturing engineering teams to analyze inline/param/probe data to identify top yield detractors and drive continuous improvement. Data Pipeline & Automation: Extract, cleanse, and analyze datasets from SQL databases, sensor networks, and fabrication tool logs to support semiconductor manufacturing operations. Advanced Analytics & Modeling: Apply data science techniques, statistical modeling, and machine learning to solve yield issues and support defect reduction strategies.
Experimentation Support: Assist process and integration engineers in running and analyzing Design of Experiments (DOE) to enhance process capabilities and margins. Visualization & Communication: Develop automated reports and dashboards using visualization tools (e.g., Dash, Plotly, Angular) to communicate technical concepts and project outcomes effectively to engineering stakeholders. Required
Qualifications
Bachelor's degree in Computer Science, Data Science, Statistics, AI, or a related Engineering field. Hands-on experience in data science, analytics, or scripting applications. Willingness to learn semiconductor manufacturing principles and collaborate closely with equipment and integration engineers to resolve production issues.
Required Technical Experience Programming & Data Engineering: Strong Python programming skills and working experience with SQL for data extraction and manipulation. Statistical Analysis: Famil
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