Principal Data Scientist

About the role

We are seeking a Principal Data Scientist to lead data‑driven initiatives in semiconductor manufacturing. You will partner with engineering teams to turn complex data streams into actionable insights that improve yield, reduce defects, and accelerate innovation.

Key responsibilities

• Yield & Process Optimization: Analyze inline, param, and 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.
• Advanced Analytics & Modeling: Apply statistical modeling and machine learning to solve yield issues and support defect‑reduction strategies.
• Experimentation Support: Assist engineers in designing, running, and interpreting Design of Experiments (DOE) to enhance process capabilities.
• Visualization & Communication: Build automated reports and dashboards (Dash, Plotly, Angular) to convey technical concepts to engineering stakeholders.

Required profile

• Bachelor's degree in Computer Science, Data Science, Statistics, AI, or a related engineering field.
• Minimum 8 years of hands‑on experience in data science, analytics, or scripting applications.
• Willingness to learn semiconductor manufacturing principles and collaborate closely with equipment and integration engineers.

Required skills

• Python programming
• SQL for data extraction and manipulation
• Statistical analysis tools and methodologies (SPC, DOE, FDC/EDA)
• Data visualization frameworks (Dash, Plotly, Angular)
• Machine‑learning techniques and statistical modeling