Data Scientist

About the role

What Impact You'll Have

GRVTY is seeking a Data Scientist with a TS/SCI + Poly clearance (acceptable to this customer) to join one of our top projects in McLean, VA. The Sponsor provides data-driven business analysis to support senior organizational leaders. As such, the Data Scientist will provide support specializing in natural language processing (NLP) and associated data preparation to help identify challenges and opportunities for the Sponsor’s customers. The Data Scientist must also be experienced in areas of SQL and Python to be able to transform the Sponsor’s structured and unstructured data into clear and supported analytic insights to help customers with decision making related to production, resources and personnel. The work may be performed independently or within a team environment.

What You'll be Owning

- Working closely with the Sponsor’s data scientists and technical team to implement requirements; however, the Sponsor’s GTM will manage the priorities

- Conducting sophisticated analysis using deployed tools and natural language processing

- Analyzing large amounts of raw data, including text data, to provide business insights

- Pre-processing and/or cleaning structured and unstructured Sponsor data, including text data

- Designing and implementing advanced ETL code and table configurations for complex data sets

- Using Structured Query Language (SQL) in Sponsor’s Oracle database to develop and organize relevant information with supporting analytics

- Independently, or with a team, authoring analytic publications and produce ad-hoc reports to include data visualizations using the Sponsor’s templates

- Staying current with the Sponsor’s enterprise metadata collection tools

- Implementing the Sponsor’s existing coordination process

- Providing technical education and subject matter expertise in NLP to support Sponsor’s initiatives to staff on an ad-hoc basis

What You Must Have

- Active TS/SCI with Polygraph Clearance (acceptable to this customer)

- Demonstrated professional or academic experience performing NLP tasks, including selecting the best Python libraries for a given task, choosing appropriate pre-processing actions, performing analysis, and assessing model performance

- Demonstrated professional or academic experience using Python NLP packages such as Spacy, Gensim, or NLTK to analyze or process collections of documents

- Demonstrated professional or academic experience with deep learning frameworks such as PyTorch, Tensorflow, or Keras

- Demonstrated professional or academic experience with the HuggingFace Transformers library and hub

- Demonstrated experience creating machine learning models that conduct text classification and topic modeling in Python using standard machine learning (Scikit-learn) or deep learning models

- Demonstrated academic or professional experience using encoder-decoder and generative language models to perform NLP tasks