Natural Language Processing Scientist
United States
As a Natural Language Processing Scientist with the Leidos Innovations Center AI/ML Accelerator I work hands-on in designing, implementing, and analyzing NLP approaches that integrate, adapt, and extend novel capabilities to state-of-the-art technical challenges in competitive contract research and development programs.My day to day:- Implement several NLP libraries to include Stanford CoreNLP, Spacy, NLTK, Word2Vec and Gensim along transformer models like BERT.- Use supervised and unsupervised machine learning approaches for domain adaptation. Those approaches include named-entity recognition, sentiment analysis, information extraction, text classification, and newer NLP capabilities that are still theoretical.- Assist the technical lead supervising the technical plan and resources.- Work at the direction of a technical lead (e.g., PhD-level research scientist), and work independently on research programs and adapt NLP technologies as part of a large project addressing highly complex research challenges.- Collect and develop data sets based common to machine learning-based NLP tasks. Examples include data collection, exploration, formatting; dimension reduction; enhancing and improving data quality; and feature selection and engineering.- Adapt and extend state of the art machine learning-based technologies to support NLP tasks.