Experience with at least one of the ML related technologies (Azure ML, MLlib, H20, Scikit-learn, Tensorflow, Keras, Various R Packages)
Hands-on experience on Python for both data prep and modeling
Good understanding of a few industry domains from the business point of view
Good understanding of Big Data Architecture that enables end to end implementation of AI projects including data pipelines, compute, storage, and application workflows
Demonstrated expertise in Data Science overall workflow and methodology supporting the need to move systems into production and support.
Demonstrated client-facing experience. Ability to gather requirements and communicate model outcomes.
Good knowledge of deep learning frameworks such as Tensorflow, Keras, Pythorch, etc… and distributed analytics on edge in IoT context.
Familiarity with AWS or the Microsoft Azure platforms is a plus
Familiar with map-reduce framework, and parallel/distributed processing such as Hadoop/Spark/
Knowledge of other languages like Java, F#, C#, C++is a plus
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