Lead, NLP Data Scientist

Key Skills

Aartificial intelligence, Apache Hadoop, AWS, Azure, C++, CUDA/GPU programming, Data science techniques, Docker, Elasticsearch, Google Cloud Platform (GCP), Java Programming, Keras software library, Kubernetes-K8s, Linguistic, Linux Operating system, Machine learning techniques, Natural Language Processing (NLP), Natural Language Toolkit - NLTK, Python Programming, PyTorch, REST API, Scala Programming, SPARK Programming, TensorFlow, Unix Operating system

Job Description

The Lead, NLP Data Science will support building of AI products in Agile fashion that empower healthcare payers, providers and members to quickly process medical data to making informed decisions and overall reduce health care costs. As a research scientist/engineer part of Data Science and Artificial Intelligence team you will be working primarily on unstructured text data to build machine learning models for information retrieval applications. These applications include but are not limited to optical character recognition, understanding the contents of the medical documents using natural language processing with help of large language models, and integrating processes into the overall AI pipeline to mine healthcare and medical information with high recall and other relevant metrics. We ingest claims, medical charts, etc. from providers containing unstructured data which will be transformed into structured data to support automated entry into our storage layers for downstream applications and automated assessment against medical policies. The results will be used dually for real-time operational processes with both automated and augmented human-based decision making (i.e., copilot tools) to reduce healthcare administrative costs. We work with all major cloud and big data vendors offerings including but not limited to (Azure, AWS, Google, IBM, etc.) to achieve AI goals in healthcare and support Evolent business.

Essential functions

The Lead, NLP Data Science will have the opportunity to build 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 Evolent 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
• Research, design, and implement innovative approaches utilizing state of the art Transformer models, large language models (like BERT, OpenAI) and generative AI techniques to solve complex healthcare challenges
• 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, trax (2+ years)

• Hands on experience with libraries and tools like Spacy, NLTK, Stanford core NLP, Genism, johnsnowlabs (5+ years)
• Staying up-to-date with advancements in AI, NLP and generative modelling to ensure our solutions remain stable and state-of-the-art.
• Rapidly prototyping ideas, approaches, and methods in AI Space
• Experience with data visualization tools to communicate insights effectively
• Work closely and collaborate with Data Scientists, Machine Learning engineers, IT teams and Business stakeholders spread 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
• 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

Academic Qualifications:

• Master’s degree or above in Computer Science, Computational Linguistics, Mathematics, Physics, or Electrical Engineering with research experience from a strong academic program along with thesis (no undergraduate degrees)
• Completion of thesis/research is required as part of graduation in computer science, artificial intelligence, Mathematics, Physics, Electrical Engineering or statistics 

Nice to Have

• A PhD degree in Computer Science, Artificial Intelligence, Computational Linguistics, Machine Learning, or related technical field from a strong academic program
• Medical concepts with codes from standard ontologies (SNOMED CT, LOINC, RxNorm, ICD, etc.)
• Experience with Huggingface Library
• Lucene, Solr, Elastic Search experience
• Experience with Kubernetes and dockers
• Experience building REST API’s for AI work and knowledge of microservices architecture
• Participation in open source community projects
• Publication record in top NLP conferences (NIPS, ICLR, ACL, NAACL, EMNLP, SIGIR, WWW, etc.)