Senior Data Scientist (NLP and Unstructured Data Analytics

Senior Data Scientist (NLP and Unstructured Data Analytics)

Location:

Herndon, VA (Remote Work)

Must have a Public Trust Clearance

Key Responsibilities

• Integrate and scale natural language processing methods to parse, clean, and analyze large corpora of unstructured and semi structured text, using optical character recognition, semantic similarity algorithms, and large language models as needed.
• Design, develop, test, calibrate, and implement statistical and machine learning models targeting financial fraud, improper payments, and non compliance within SBA programs.
• Build and refine supervised and unsupervised models, including regression, Bayesian, clustering, and ensemble approaches.
• Review, maintain, and support all existing loan fraud indicators developed by TSD.
• Perform data quality analysis on source tables and develop repeatable processes for combining and analyzing large data sources.
• Collaborate directly with criminal investigators to determine and execute analytic strategies supporting loan fraud cases, and adhere closely to the federal rules of criminal procedure governing protected information, including Rule 6(e).
• Develop case leads for SBA OIG investigations from model outcomes.
• Document all methodology, test models, and production models in a form that satisfies criminal evidentiary requirements.
• Build visualizations and dashboards conveying methodological choices, outcomes, and predictive capability, iterated on end user feedback.
• Deliver findings in multiple registers: data summaries and visualizations for investigative staff, executive summaries for OIG leadership.
• Coordinate with the data engineering seat so the architecture supports machine learning and text processing pipelines efficiently.
• Create programming and automation techniques using SharePoint, Python, Excel, Power BI, Power Apps, and similar tools.
• Identify new business questions that expand the scope of analysis and reporting.