Principal Data Scientist

Key Responsibilities

• Lead the design, development, and deployment of high-fidelity digital twin models for semiconductor fab operations, enabling accurate representation of WIP flow, equipment behavior, capacity constraints, and factory dynamics.
• Develop advanced discrete-event, agent-based, or hybrid simulation frameworks to analyze cycle time, throughput, bottlenecks, and scheduling scenarios across complex manufacturing systems.
• Drive AI- and ML-enhanced simulation methodologies, including predictive modeling, prescriptive analytics, reinforcement learning, and optimization algorithms to improve factory performance and decision-making.
• Collaborate closely with Operations, Industrial Engineering, Manufacturing, and Data Science teams to translate operational challenges into simulation experiments and data-driven solutions.
• Build and maintain scalable simulation architectures that integrate real fab data (MES/EWS, equipment logs, sensor/IoT data) for continuous model calibration and accuracy improvement.
• Develop scenario analysis and 'what-if' studies to support capacity planning, equipment purchase decisions, technology transitions, dispatching strategy evaluation, and cycle-time reduction initiatives.
• Lead the creation of predictive and prescriptive decision-support systems, combining simulation, optimization, and machine learning to enhance scheduling, resource allocation, and operational agility.
• Own end-to-end model validation and verification, ensuring technical robustness, traceability, and alignment with fab behavior and factory physics.
• Partner with IT/OT teams to operationalize digital twin models, integrating simulation capability into production environments and enabling real-time or near-real-time decision intelligence.
• Mentor and guide junior engineers and data scientists, fostering technical excellence and best practices across modeling, simulation, and advanced analytics.
• Communicate insights, model results, and recommendations to technical and non-technical stakeholders through clear reports, presentations, and dashboards.
• Continuously evaluate emerging technologies in simulation, AI, optimization, and digital twin platforms to drive innovation and maintain competitive advantage for Micron’s smart manufacturing strategy.