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| Job Location | Bangalore |
| Education | Not Mentioned |
| Salary | Not Disclosed |
| Industry | Consumer Durables / Electronics |
| Functional Area | Sales / BD |
| EmploymentType | Full-time |
Applied Research team at Swiggy is looking for experienced researchers with an aptitude to solve challenging real-world problems in the area of natural language processing ( NLP)/natural language understanding ( NLU).Role Summary:- As a Data Scientist II, we are looking for someone with strong expertise in Deep Learning and NLP. You would be working on some of the important problem statements we are trying to solve : developing chatbot for English and mixed English ( English and Indian languages written using English keyboards), intent classification, sentiment analysis, text categorization, keyword spotting, machine translation from English to Indian languages and vice-versa, automatic speech recognition ( ASR) etc. What do we look forThe potential candidates need to be well versed in classical text processing methodologies like hidden Markov models ( HMMs), conditional random fields ( CRFs), topic models, word-embeddings, part-of-speech ( PoS) tagging etc. Good understanding of usual machine learning ( ML) tools is very important. Hands-on experience of deep learning ( DL) techniques like convolutional neural networks ( CNNs), recurrent neural networks ( RNNs), long-term short-term memory ( LSTM) etc is essential. Hands-on coding experience in ML friendly languages like python and knowledge of open source ML/DL libraries is needed in order to implement the ideas into working proof-of-concepts ( PoCs). The right candidate will have masters ( M.S./ M.Tech . etc) or/and PhD degrees with research experience of 4 years in some of the above domains. Preferably should have published their research in conferences and journals of repute. Swiggy is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce.,
Keyskills :
machinelearning python dataanalysis sql analytics hiddenmarkovmodels naturallanguageprocessing opensource deeplearning markovmodels naturallanguage appliedresearch codingexperience euralnetw ks sent