Senior Data Scientist NLU/ NLP

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Senior Data Scientist NLU/ NLP

Decision Engines AI

Hyderabad INR 25 - 35 LPA Experience : 6 - 20 YRS. Openings: 1

Details:

  • Hands-on skills with complex Machine learning / Deep learning-based techniques and frameworks for optimal accuracy and performance in big production systems using Python
  • Experience building custom NER, Q&A, and Intent Analysis algorithms
  • Experience in building Ontologies and knowledge graphs and ability to build NL query parsers
  • Experience with complex RNN / LSTM / Encoder-Decoder deep learning architectures.
  • Experience with TensorFlow,PyTorch etc.
  • Data-driven,with demonstrable rigor in test and training data management.
  • Experience filing patents.Major journal publications a plus
  • The position is based out of Hyderabad, India and the candidate must be willing to relocate to Hyderabad post-COVID-19.

Min. Qualification:

Masters Computer Science/ Operations Research / Optimization or  equivalent field with 2+ years of relevant experience or Ph.D. in Computer Science/ Operations Research / Optimization or  equivalent field with an emphasis in Artificial Intelligence and Natural Language Processing


Skills Required:

Python, TensorFlow, PyTorch

Roles:

As a Senior Data Scientist,

  • You’ll work with our team to create models that extract data from unstructured and semi-structured data sources,models that use natural language queries for extracting relational data from disparate sources,
    and model learning systems that emulate business process decisions end-to-end.
  • We deal with a large number of known problems with NLP such as relation extraction, NER, cross-document summarization, natural language understanding, natural language generation, topic modeling, and entity linking/disambiguation.
  • Your job includes developing new technologies, improving on existing technologies, and building these tools into enterprise-level software.
  • You will be both hands-on and strategic—with both a broad ecosystem-level understanding of our market space andthe ability to work closely with engineering and product teams to deliver software in an iterative, continual-release environment.

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