Data Scientist SMART Manufacturing & AI

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., Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.

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• 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 in Japanese.
• Experience with or desire to learn:
• Machine learning and other advanced analytical methods
• Fluency in Python and/or R
• pySpark and/or SparkR and/or SparklyR
• Hadoop (Hive, Spark, HBase)
• Teradata and/or another SQL databases
• Tensorflow, and/or other statistical software including scripting capability for automating analyses
• SSIS, ETL
• Javascript, AngularJS 2.0, Tableau
• 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
• Bachelor degree or equivalent experience

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