Data Scientist - Speech & Text Analytics


Job Description

Candidate should be able to:
- Build text-based search engine and question answering system for Q Degrees
-utilize the latest techniques in AI, ML (including Deep Learning approaches) and NLU
- Build voice-based search engine and question answering system for Q Degrees
- Build topic analysis, voice recognition, text classification, named entity recognition methods for unstructured and semi-structured data
- Generate creative solutions in the field of Voice Bots and Chat Bots (patents) and publish research results in top conferences (papers)
- Perform voice/text mining, generate and test working hypotheses, prepare and analyze historical data and identify patterns
-part of a project team, to lead Speech Text Bots for the next generation of intelligence and language understanding for better Consumer Insights
Candidate should have:
- Experience with data structures and algorithms; Ability to work in a Unix environment and building robust data processing and analytics pipelines
- Should be comfortable working with structured Unstructured Data.
- Excellent background in Machine Learning (generative model, discriminative model, neural network, regression, classification, clustering, etc.)
- Experience in Developing and Deploying Voice Bots
- Have experience in developing Speech Bots / Speech to Text Models
- Experience in applied statistics including sampling approaches, modeling, and data mining techniques
- Extensive experience in using NLP-related techniques/algorithms such as HMM, CRF, deep learning recurrent ANN, word2vec/doc2vec, Bayesian modeling, etc.
- Contributions to research communities, e.g. ACL, NIPS, ICML, EMNLP, etc. is a Plus
- Ability to work as ICR in coordination with existing IT developers
- Ability to work independently under tight deadlines with accountability.
- Strong results-driven personality with a high level of enthusiasm, energy, and confidence.
- Strong problem-solving skills.
- In-depth knowledge of various Natural Language Processing/Understanding (NLP/NLU) domains such as entity extraction, speech recognition, topic modeling, parsing, question answering, Relation Extraction, Ontology, etc.
  • NLP
  • HMM
  • CRF
  • deep learning recurrent ANN
  • word2vec/doc2vec
  • Bayesian modeling

Key Skills

Unix; Text mining; deep learning; Machine learning; Data processing; Data structures; Natural language processing; Data mining; Analytics; text analytics

About Company

Anicalls India Pvt Ltd

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