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Senior Data Scientist (NLP and Unstructured Data Analytics)

Remote in Washington, DC, US • Posted 2 hours ago • Updated 2 hours ago

Full Time

On-site

Fitment

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Job Details

Skills

Unstructured Data
Analytics
Security Clearance
Semantics
Algorithms
Payments
Regulatory Compliance
Ensemble
Data Quality
Collaboration
Dashboard
Leadership
Data Engineering
Microsoft SharePoint
Microsoft Excel
Microsoft Power BI
Reporting
Data Science
Machine Learning (ML)
Computer Science
Mathematics
Artificial Intelligence
Management
Analytical Skill
Regression Analysis
Statistical Models
Finance
Fraud
Python
Pandas
Data Analysis
SQL
Microsoft SQL Server
PostgreSQL
Natural Language Processing
Presentations
Named-Entity Recognition (NER)
Semantic Search
Large Language Models (LLMs)
Optical Character Recognition
Modeling
Clustering
Auditing
Legal
Cloud Computing
Microsoft Azure
Amazon Web Services
Google Cloud
Google Cloud Platform
Online Training

Unstructured Data
Analytics
Security Clearance
Semantics
Algorithms
Payments
Regulatory Compliance
Ensemble
Data Quality
Collaboration
Dashboard
Leadership
Data Engineering
Microsoft SharePoint
Microsoft Excel
Microsoft Power BI
Reporting
Data Science
Machine Learning (ML)
Computer Science
Mathematics
Artificial Intelligence
Management
Analytical Skill
Regression Analysis
Statistical Models
Finance
Fraud
Python
Pandas
Data Analysis
SQL
Microsoft SQL Server
PostgreSQL
Natural Language Processing
Presentations
Named-Entity Recognition (NER)
Semantic Search
Large Language Models (LLMs)
Optical Character Recognition
Modeling
Clustering
Auditing
Legal
Cloud Computing
Microsoft Azure
Amazon Web Services
Google Cloud
Google Cloud Platform
Online Training

Summary

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.

Requirements

Required

Education

Master's, Ph.D., or doctorate level equivalent degree in data science, machine learning, computer science, mathematics, or a related field. Alternatively, ten years of applied work experience in any of the same fields.

5+ years Designing, implementing, and maintaining advanced AI systems and predictive models, including both supervised and unsupervised models.
5+ years Developing analytic rules and models using leading edge analytic tools and best practices.
5+ years Developing regression, classification, and other statistical models to identify anomalies, patterns, and predictive variables.
3+ years Providing data support for criminal investigations into financial fraud or abuse of government funds.
3+ years Manipulating data in Python. Pandas is required.
3+ years Working in a modern cloud environment: Azure, AWS, or Google Cloud Platform. Certifications preferred.
2+ years Conducting advanced data analysis in SQL, specifically SQL Server and PostgreSQL.
2+ years Developing and scaling natural language processing solutions.
2+ years Presenting methods and findings to technical and non technical stakeholders, both orally and in written products and visualizations.

PREFERRED QUALIFICATIONS

Production experience with named entity recognition and entity resolution across messy document corpora.
Retrieval augmented generation, vector stores, embeddings, and semantic search at scale.
Large language model integration under federal security constraints, including boundary controlled deployment and prompt versioning.
Optical character recognition pipelines applied to scanned or low quality source documents.
Topic modeling, document classification, or clustering applied to audit, legal, or investigative text.
Cloud certification in Azure, AWS, or Google Cloud Platform.

Benefits

We are proud to offer competitive compensation and benefits packages to include

Medical
Dental
Vision
Basic Life
Health Saving Account
401K matching
Three weeks of PTO/Sick
11 Paid Holidays
Pre-Approved Online Training

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91022750
Position Id: 3d40fc16c341b9b2284929b3cd633947
Posted 2 hours ago

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