Data Scientist- NLP/Text Mining

Job description
The Sr. NLP Text Mining Scientist / Engineer will have the opportunity to lead a team, shape team
culture and operating norms as a result of the fast-paced nature of a new, high-growth
organization.
• 7+ years of Industry experience primarily related to Unstructured Text Data and NLP
(PhD work and internships will be considered if they are related to unstructured text
in lieu of industry experience but not more than 2 years will be accounted towards
industry experience)
• Develop Natural Language Medical/Healthcare documents comprehension related
products to support Health business objectives, products and improve
processing efficiency, reducing overall healthcare costs
• Gather external data sets; build synthetic data and label data sets as per the needs
for NLP/NLR/NLU
• Apply expert software engineering skills to build Natural Language products to
improve automation and improve user experiences leveraging unstructured data storage, Entity Recognition, POS Tagging, ontologies, taxonomies, data mining,
information retrieval techniques, machine learning approach, distributed and cloud
computing platforms
• Own the Natural Language and Text Mining products — from platforms to systems
for model training, versioning, deploying, storage and testing models with creating
real time feedback loops to fully automated services
• Work closely and collaborate with Data Scientists, Machine Learning engineers, IT
teams and Business stakeholders spread out across various locations in US and India
to achieve business goals
• Provide mentoring to other Data Scientist and Machine Learning Engineers
• Strong understanding of mathematical concepts including but not limited to linear
algebra, Advanced calculus, partial differential equations and statistics including
Bayesian approaches
• Strong programming experience including understanding of concepts in data
structures, algorithms, compression techniques, high performance computing,
distributed computing, and various computer architecture
• Good understanding and experience with traditional data science approaches like
sampling techniques, feature engineering, classification and regressions, SVM, trees,
model evaluations
• Additional course work, projects, research participation and/or publications in
Natural Language processing, reasoning and understanding, information retrieval,
text mining, search, computational linguistics, ontologies, semantics
• Experience with developing and deploying products in production with experience
in two or more of the following languages (Python, C++, Java, Scala)
• Strong Unix/Linux background and experience with at least one of the following
cloud vendors like AWS, Azure, and Google for 2+ years
• Hands on experience with one or more of high-performance computing and
distributed computing like Spark, Dask, Hadoop, CUDA distributed GPU (2+ years)
• Thorough understanding of deep learning architectures and hands on experience
with one or more frameworks like tensorflow, pytorch, keras (2+ years)
• Hands on experience with libraries and tools like Spacy, NLTK, Stanford core NLP,
Genism, johnsnowlabs for 5+ years
• Understanding business use cases and be able to translate them to team with a
vision on how to implement
• Identify enhancements and build best practices that can help to improve the
productivity of the team.