Data Scientist Expert

Rapid Cycle Solutions, LLC•McLean, VA

4d•Onsite

About The Position

Data Scientist Rapid Cycle Solutions LLC (RCS) is an innovative small business providing IT and management consulting services to the U.S. Federal Government and commercial clients. We have unique strengths in complex, cross-organizational solution analysis, design, development, implementation, and change management supporting enterprise requirements. Our team of professionals has deep consulting backgrounds supporting the unique needs of our clients. Our team members have proven experience leading strategic initiatives within the civilian Government agencies. Note: Please ensure you meet the Security Clearance obligations before applying to optimize your consideration for this and other employment opportunities with RCS. RCS is seeking a Data Scientist to provide data-driven business analysis to support senior organizational leaders. It requires support specializing in natural language processing (NLP) and associated data preparation to help identify challenges and opportunities for the customers. SQL and Python skills to transform the 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. This position requires the candidate to meet specific Security Clearance obligations to work onsite in McLean, VA.

Requirements

Active TS/SCI clearance with Full Scope Polygraph
U.S. Citizenship required (NO EXCEPTIONS)
Perform NLP tasks, including selecting the best Python libraries for a given task, choosing appropriate pre-processing actions, performing analysis, and assessing model performance.
Using Python NLP packages such as Spacy, Gensim, or NLTK to analyze or process collections of documents.
Deep learning frameworks such as PyTorch, Tensorflow, or Keras.
Experience with the HuggingFace Transformers library and hub.
Creating machine learning models that conduct text classification and topic modeling in Python using standard machine learning (Scikit-learn) or deep learning models.
Using encoder-decoder and generative language models to perform NLP tasks.
Communicating methodological choices and model results.
Proficiency with SQL to include using common table expressions, set operations, aggregated functions and nested subqueries.
Experience with version control systems such as GitHub and Jenkins.
Leveraging GPUs for accelerated computing.
Practical approaches for measuring performance.
Assist in developing types of measure, the collection of data, analyzing the data, and presenting that data to senior leadership.
Conduct advanced statistical analysis on personnel, intelligence, and performance metrics.
Assist in selection or development of appropriate methodology to conduct research.
Analyze information and provide research findings in a manner that is easily grasped.

Nice To Haves

Writing Python scripts that pull data from web-based APIs and relational databases.
Cloud computing development and architecture
Front-end web development frameworks such as Flask.
Developing applications for semantic search.
Tuning LLMs on custom data sets and applying results to specific use cases.
Proficiency with Tableau to produce visualizations and dashboards.

Responsibilities

Work closely with the data scientists and technical team to implement requirements; however, the GTM will manage the priorities.
Conduct sophisticated analysis using deployed tools and natural language processing.
Analyze large amounts of raw data, including text data, to provide business insights.
Preprocess or clean structured and unstructured data, including text data.
Design and implement advanced ETL code and table configurations for complex data sets.
Use Structured Query Language (SQL) in Oracle database to develop and organize relevant information with supporting analytics.
Independently, or with a team, author analytic publications and produce ad-hoc reports to include data visualizations using the templates.
Stay current with the enterprise metadata collection tools.
Implement the existing coordination process.
Provide technical education to staff on an ad-hoc basis.
Provide subject matter expertise in NLP to support initiatives.