About the role
AI summarisedThis Data Scientist role at Micron involves developing predictive models and actionable insights for highly automated semiconductor manufacturing operations. The candidate will design and deploy computer vision and optimization models, working cross-functionally with data engineers and business teams to solve complex industrial problems.
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Key Responsibilities
- Employ techniques and theories drawn from areas of mathematics, statistics, semiconductor physics, materials science, and information technology to uncover patterns in data.
- Interact with experienced Data Scientists, Data Engineers, Business Areas Engineers, and UX teams to identify questions and issues for data analysis projects.
- Help develop software programs, algorithms and/or automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources.
- Perform exploratory and new solution development activities for predictive models and actionable insights.
- Design and deploy computer vision models for object detection, image segmentation and anomaly detection.
- Stay abreast of the latest research and advancements in machine learning and computer vision and apply them to real-world problems.
- Coordinate production deployment activities, including cross-functional communications, approval and execution of changes in live environments.
Requirements
- Master/PHD Degree in Operation Research, Industry Engineering, Statistics with a strong academic foundation in linear programming and optimization.
- Minimum 3 years of experience in operation research/optimization, preferably with working experience in the semiconductor industry.
- Strong foundation in Linear programming optimization modeling, advanced analytics, and machine learning techniques.
- Experience in computer vision, statistical modeling, deep learning, generative AI, feature extraction and analysis, supervised/unsupervised/semi-supervised learning.
- Ability to extract data from multiple databases using SQL and other query languages, including experience with data cleansing, outlier detection, and handling missing data.
- Strong proficiency in Python and linear programming, SQL, C#.
- Proficiency in data visualization tools such as Tableau, Power BI, and related techniques.
- Proficiency in web development technologies, including Angular, FastAPI, and Docker.
- Strong verbal and written communication skills.
- Strong desire to grow a career as a Data Scientist in highly automated industrial manufacturing doing analysis and machine learning on terabytes and petabytes of diverse datasets.