Senior Data Scientist (Nlp And Unstructured Data Analytics)

Node.Digital

  • Washington, DC
  • 1 day ago
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    Skills

    • Algorithmsunmatched
    • Amazon Web Services (AWS)unmatched
    • Analysis Skillsunmatched
    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Bayesian Networksunmatched
    • Best Practicesunmatched
    • Cloud Computingunmatched
    • Compensation and Benefitsunmatched
    • Computer Scienceunmatched
    • Customer/Client Researchunmatched
    • Data Analysisunmatched
    • Data Qualityunmatched
    • Data Scienceunmatched
    • Data Visualizationunmatched
    • Financial Fraudunmatched
    • Financial Modelingunmatched
    • Fraud Investigationunmatched
    • GCP (Good Clinical Practices)unmatched
    • Government Fundingunmatched
    • Information/Data Security (InfoSec)unmatched
    • Leadershipunmatched
    • Machine Learningunmatched
    • Mathematicsunmatched
    • Microsoft SQL Serverunmatched
    • Microsoft SharePointunmatched
    • Microsoft Windows Azureunmatched
    • Modeling Languagesunmatched
    • Natural Language Processing (NLP)unmatched
    • Online Trainingunmatched
    • PostgreSQLunmatched
    • Power BIunmatched
    • Predictive Modelingunmatched
    • Process Developmentunmatched
    • Programming Methodologiesunmatched
    • Python Programming/Scripting Languageunmatched
    • Reporting Dashboardsunmatched
    • SQL (Structured Query Language)unmatched
    • Semantic Searchunmatched
    • Small Businessunmatched
    • Statistical Modelingunmatched
    • Systems Maintenanceunmatched
    • Test Plan/Scheduleunmatched
    • Unstructured Dataunmatched

    Description

    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 GCP. 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 GCP.

    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

    Numbers & Facts

    LocationWashington, DC

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