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Director, Data Science
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- Solves business problems — Business to Consumer (B2C), Business to Business (B2B), quality operations, operations management, and automation — using Artificial Intelligence (AI) and data science techniques (Natural Language Processing (NLP), DL, ML, causal inference, predictive analytics, experimental design, and optimization).
- Leads the design and development of innovative solutions for customer and associate-centric projects text mining, document/image processing, and document-processing workflows.
- Bachelor s degree (or foreign education equivalent) in Applied Mathematics, Computer Science, Engineering, Information Technology, Information Systems, Information Management, Mathematics, or a closely related field and five (5) years of experience as a Director, Data Science (or closely related occupation) launching, operating, leading and implementing document processing, computer vision, and Deep Learning (DL) practices using TensorFlow, Keras, MXNET, or H2O.
- Or, alternatively, Master s degree (or foreign education equivalent) in Applied Mathematics, Computer Science, Engineering, Information Technology, Information Systems, Information Management, Mathematics, or a closely related field and two (2) years of experience as a Director, Data Science (or closely related occupation) launching, operating, leading and implementing document processing, computer vision, and Deep Learning (DL) practices using TensorFlow, Keras, MXNET, or H2O.
- Demonstrated Expertise (“DE”) developing semi-supervised, supervised, and unsupervised Machine Learning (ML) (in Python) and Deep Learning (DL) models (in PyTorch); applying functional paradigms Haskell to build composable learning systems and products; and performing probabilistic modeling, using PyStan, PyMC3, and Pyro.
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