Senior Data Scientist, Global Operations Intelligence

About the role

Micron is hiring a Senior Data Scientist for its Global Operations Intelligence team (SMAI) at Fab 10A. The role applies mathematical optimization, machine learning and data-driven analytics to improve semiconductor manufacturing capacity, throughput and decision quality.

Key responsibilities

• Develop optimization models for capacity utilization, throughput, cycle time, tool loading and bottleneck management, and build models for capacity planning, production allocation and investment prioritization.
• Apply operations research techniques such as linear programming, mixed-integer programming, constraint programming, stochastic optimization and simulation-based optimization.
• Design algorithms supporting factory maxout strategies and identify ways to unlock capacity without extra capital investment.
• Partner with manufacturing, industrial engineering, planning, equipment, process and business teams to analyze tool capability, process flows, WIP movement, cycle time and dispatching rules, and support scenario analysis for capacity expansion, product mix changes and technology transitions.
• Build predictive and prescriptive models using large-scale manufacturing and planning data, and integrate optimization engines with dashboards and decision-support tools.
• Work with software engineering teams to deploy scalable models into production systems.
• Translate findings into clear insights for technical teams and business leaders, quantify business impact (capacity gain, cost avoidance, cycle time reduction, productivity, capital efficiency) and contribute to the roadmap for capacity intelligence, factory digital twin and AI-driven planning.

Required profile

• Master's degree or higher in a quantitative field such as Electrical Engineering, Statistics, Mathematics or a related discipline.
• Experience with mathematical optimization, statistical modeling, machine learning, reinforcement learning and algorithm development.
• Experience designing and evaluating reinforcement learning models, MDPs and learning-based decision systems, and building simulation pipelines and large-scale numerical experiments.
• Strong written and verbal communication, shown through peer-reviewed publications and the ability to turn analytical results into actionable insights.
• Preferred: PhD in Operations Research, Industrial Engineering, Applied Mathematics or Systems Engineering; semiconductor manufacturing experience; hands-on experience with discrete-event or factory simulation platforms; experience deploying optimization or AI/ML models in production; knowledge of MES, ERP, APS, data warehouses or planning platforms; experience leading analytical projects from problem definition to adoption.

Required skills

• Programming: Python, R, MATLAB, SQL, Spark, Git
• Optimization: LP, MILP, nonlinear optimization, constraint programming, stochastic optimization; tools: Gurobi, CPLEX, OR-Tools, Pyomo, PuLP
• Data science: regression, classification, clustering, time-series forecasting, anomaly detection, predictive modeling
• Simulation: discrete-event simulation, what-if analysis, scenario modeling, digital twin concepts
• Visualization: Power BI, Tableau, Plotly, Dash or equivalent