As a Data Science Engineer at Micron, you will employ techniques and theories drawn from areas of mathematics, statistics, semiconductor physics, materials science, and information technology to uncover patterns in data from which predictive models, actionable insights, and solutions can be developed.

You will interact with experienced Data Scientists, Data Engineers, Business Areas Engineers, and UX teams to identify questions and issues for data analysis projects and improvement of existing tools. In this position, you will help develop software programs, algorithms and/or automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources. There will be significant opportunities to perform exploratory and new solution development activities.

Responsibilities include, but not limited to:
• 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.
• Experience in the areas: statistical modeling, feature extraction and analysis, supervised/unsupervised/semi-supervised learning. Exposure to the semiconductor industry is a plus but not a requirement.
• Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques.
• Strong software development skills.
• Strong verbal and written communication skills.
• Experience with or desire to learn
• Machine learning and other advanced analytical method
• Familiar CNN, RNN, GAN, etc.
• Fluency in Python and Machine learning, Deep learning.
• GCP, snowfalke, SQL Server or another SQL databases
• Tensorflow, and/or other statistical software including scripting capability for automating analyses
• Javascript, Tableau, Power BI,
• Experience working with time-series data, images, semi-supervised learning, and data with frequently changing distributions is a plus
• Experience working with Manufacturing Execution Systems (MES) is a plus
• Existing papers from CVPR, NIPS, ICML, KDD, and other key conferences are plus, but this is not a research position

Education:
• B.S. in Mathematics, Computer Science, Data Science and Physics.
• M.S. or Ph.D. with specialization in Data analytics, mathematics, Physics, Statistics, computer science.

Experience:
• 2+ years to data science and machine learning.