About the role
AI summarisedAs a Senior Data Scientist in Smart Manufacturing & AI at Micron, you will develop data-driven solutions to improve semiconductor manufacturing yield, quality, and productivity. You will apply optimization, mathematical programming, and machine learning to large-scale manufacturing data, collaborating with cross-functional teams to build and deploy analytical models into production systems. The role involves end-to-end data science workflows, from data extraction and feature engineering to model monitoring and communication of insights to technical and non-technical stakeholders.
IDMOnsiteSmart MFG/AI
Key Responsibilities
- Design, develop, and deploy operation research, optimization and mathematical programming solutions to support intelligent decision making in advanced manufacturing workflows
- Build and productionize machine learning models (classification and regression) to support predictive and prescriptive analytics across semiconductor test and manufacturing processes
- Perform end-to-end data science workflows, including data extraction, feature engineering, model development, validation, deployment, and ongoing monitoring
- Analyze large, complex, and heterogeneous datasets sourced from multiple manufacturing systems, applying data cleansing, outlier detection, and missing-data handling techniques
- Partner with product/test engineers, business collaborators, product owners, and IT teams to define analytical problem statements, success metrics, and scalable solution architectures
- Develop robust, maintainable software and analytical pipelines suitable for high-volume manufacturing environments
- Clearly communicate analytical insights, model behavior, and trade-offs to both technical and non-technical customers to enable data-driven decisions
Requirements
- Bachelor's degree in computer science, data science, operations research or equivalent
- Strong desire to grow a career as a Data Scientist in advanced, highly automated industrial manufacturing
- Solid foundation in optimization, mathematical programming, statistics, and/or machine learning, with practical experience applying these techniques to real-world data
- Experience with supervised and unsupervised learning, feature extraction, and model evaluation
- Proficiency in Python, with strong software development and coding using best practices
- Experience extracting and manipulating data using SQL and other query languages
- Strong verbal and written communication skills, with the ability to explain complex analytical results clearly
- Experience or strong interest in advanced machine learning and large-scale analytics
- Experience or strong interest in optimization algorithms (e.g., linear programming, integer programming, heuristics, constraint-based optimization)
- Familiarity with TensorFlow or similar machine learning frameworks
- Familiarity with ETL and data integration tools
- Familiarity with data visualization and UI technologies (e.g., Tableau)
- Exposure to time-series data, manufacturing data with frequently changing distributions, or semi-supervised learning