AI Data Scientist Technical Leader

What you'll do

• Develop, deploy, and maintain AI/ML models for yield analysis and early-stage failure prediction.
• Build and optimize AI agents to automate data-driven root cause analysis and yield improvement.
• Analyze large-scale manufacturing, test, and parametric datasets to identify trends and anomalies.
• Design and implement predictive models to forecast yield and quality metrics throughout the manufacturing flow.
• Translate business and technical requirements into robust data science solutions for hardware and process engineering teams.
• Communicate findings and recommendations to multi-functional teams through clear visualizations, reports, and presentations.

What we're looking for

• MS or PhD in Computer Science, Electrical Engineering, Data Science, Statistics, or a related field.
• 8+ years of experience in data science, machine learning, or data analytics.
• Experience in semiconductor or hardware engineering environments (preferred).
• Strong proficiency in Python and data science libraries like pandas, scikit-learn, XGBoost, TensorFlow, and PyTorch.
• Experience building, validating, and deploying AI/ML models for classification, regression, anomaly detection, and time-series forecasting.
• Hands-on experience with AI agent frameworks and automation of data analysis workflows.
• Solid understanding of semiconductor manufacturing, test data, and yield analysis concepts.
• Experience with data visualization tools such as matplotlib, seaborn, Tableau, or Power BI.
• Experience with cloud-based data platforms and big data technologies (preferred).
• Familiarity with Optuna or other hyperparameter optimization frameworks (preferred).
• Knowledge of hardware debug, root cause analysis, and reliability engineering (preferred).