Pre-processing
Demonstrate the skills and experience to collect, clean, and prepare data sets for input into a computational model using Python
Strong candidates will explain various methods you have applied using common pre-processing functions such as stop word removal, stemming, lemmatization, and tokenization
Feature Engineering and Attribute Evaluation
Candidate must demonstrate experience with NLP feature engineering methods such as TF-IDF, word2vec, GloVe, and FastText identifying the key determinants for modeling that exist in the business process and within existing data sets as well as selecting evaluation protocols (model techniques)
Modeling
Candidates will have practiced skills and experience selecting classification modeling techniques to fit the business problem. Examples will include techniques such as machine learning (ML) supervised and unsupervised learning, regression, neural networks and deep learning, natural language processing, etc.
Validation
Strong candidates will describe their experience with investigating, reporting, and justifying model results
Visualization
Experience in presenting the results of their modeling activities, depicting the insights realized, and explaining the relevance of their results to the organization’s business challenges

Master's degree required, and PhD preferred in Statistics, Mathematics, Computer Science, or similar
High degree of experience utilizing SAS, R, or Python to support NLP use cases such as Document Summarization, Named Entity Recognition, Sentiment Analysis, and/or Topic Modeling
At least four years of experience developing scalable, production-ready NLP solutions using sci-kit learn, Keras, TensorFlow, PyTorch, Spark NLP
Experience using git/github to version control source code
Experience leveraging transformer architecture to develop NLP models
Experience with open source NLP packages such as Gensim, SpaCy, or NLTK
Experience with BERT, GPT-J, RoBERTa, T5 or other transformers
Experience with GenAI and Prompt Engineering is a plus
Experience in Databricks and MLFlow is a plus
Experience with machine translation and transcription of foreign language documents using Microsoft Azure translation services is a plus
Experience working in an AWS cloud environment and with related AWS services such as Bedrock and Textract
Experience coordinating and maintaining user stories
Must be a US citizen
Must be able to obtain and maintain a Public trust security clearance

Data Scientist – NLP

Key skills