Senior Data Scientist

Responsibilities include, but not limited to: Work with an international team of data scientists, data engineers, solution architect, external solution provider, and our stakeholders in construction, facility, planning teams in a collaborative manner to create highly accurate digital twins of our fabs and enable more advanced capabilities, e.g., Photorealistic and physics-based simulation, etc.. Digital Twin Development Build and maintain data-driven models representing fab processes, equipment behavior, and subfab utilities. Integrate IoT sensor data, MES (Manufacturing Execution System) data, and facility data into the digital twin platform. Predictive Analytics & Machine Learning Develop algorithms for predictive maintenance , throughput optimization , and energy efficiency . Apply statistical and ML techniques to forecast equipment failures, cycle time variations, and yield impacts. Simulation & Optimization Use simulation tools (e.g., NVIDIA Omniverse) to run what-if scenarios for layout changes, capacity planning, and process improvements. Optimize fab workflows for cost, energy, and productivity. Data Integration & Visualization Design dashboards for real-time monitoring of fab KPIs (e.g., OEE, WIP, energy consumption). Collaborate with engineering teams to visualize fab layouts and operational states in 3D environments. Collaboration Work closely with process engineers, facility planners, and IT teams to ensure seamless integration of digital twin solutions. Support cross-functional projects involving AI, automation, and Industry 4.0 initiatives. Required Skills Strong proficiency in Python, R, SQL , and data engineering. Master’s/Bachelor’s degree in Operations Research, Computer Science, Data Science or other quantitative disciplines with strong emphasis on optimization, simulation, and algorithmic problem-solving. 3+ years of Experience with machine learning frameworks (TensorFlow, PyTorch) and simulation tools . Knowledge of semiconductor manufacturing processes and fab operations. Familiarity with IoT data pipelines , MES systems , and cloud platforms (AWS, Azure). Understanding of 3D modeling and visualization tools (Omniverse, Unity, or similar)