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 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
