We are seeking a creative and motivated Data Analytics & AI Specialist to join our Data & Automation team. In this role, you will develop and deploy data-driven solutions using machine learning, statistical modelling, and AI techniques to solve complex challenges across fab operations?from wafer processing and defect detection to predictive maintenance and real-time process control. You will collaborate closely with process engineers, equipment specialists, and IT teams to transform raw fab data into actionable intelligence that enhances productivity, quality, and yield.

Key Responsibilities

Design, develop, and implement scalable data pipelines to ingest, clean, and structure high-volume, high-velocity data from fab tools (e.g., sensors, MES, EDA, APC systems).

Apply advanced analytics, machine learning, and AI techniques (e.g., computer vision, time-series forecasting, anomaly detection, reinforcement learning) to improve manufacturing outcomes.

Build predictive and prescriptive models for applications such as:

• Yield prediction and root cause analysis
• Equipment health monitoring and predictive maintenance
• Real-time process control and fault detection
• Defect classification and pattern recognition
• Collaborate with cross-functional teams to translate business problems into analytical frameworks and measurable KPIs.
• Deploy and monitor ML models in production environments, ensuring reliability, scalability, and compliance with fab data governance standards.
• Stay current with emerging AI/ML technologies and assess their applicability to semiconductor manufacturing challenges.
• Document methodologies, share insights through dashboards/reports, and support continuous improvement initiatives.

Required Qualifications

• Minimal Bachelor in Data Science, Computer Science, Electrical Engineering, Industrial Engineering, Applied Mathematics, or a related field preferred.
• 2+ years of experience applying data analytics and/or machine learning in semiconductor manufacturing or fab automation.
• Knowledge of semiconductor processes (e.g., lithography, etch, deposition) or equipment data standards (SECS/GEM, GEM300)
• Strong programming skills in Python (pandas, scikit-learn, TensorFlow/PyTorch) and SQL.
• Experience working with time-series data, sensor data, or structured/unstructured manufacturing data.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and big data tools (e.g., Spark, Kafka).
• Understanding of statistical methods, experimental design, and model validation techniques.
• Excellent problem-solving, communication, and teamwork skills.