Senior NLP Data Scientist — Unstructured Data Analytics

Node.Digital LLC

Herndon (VA)

Hybrid

USD 150,000 - 190,000

Full time

14 days+

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Benefits offered by this job

Medical

Dental

Vision

Basic Life

Health Saving Account

401K matching

Three weeks of PTO/Sick

11 Paid Holidays

Pre-Approved Online Training

Job summary

Senior Data Scientist (NLP and Unstructured Data Analytics) in Herndon, VA with Remote Work option. Must have a Public Trust Clearance. Responsibilities include NLP integration, ML model development for fraud detection, and collaboration with investigators under federal rules.

Strong Python, NLP, cloud, and data visualization skills required; experience with OCR, LLMs, and dashboards is essential. Education requires a Master’s/PhD or 10 years of related work; preferred cloud certifications and

Qualifications

Master's, Ph.D., or doctorate level equivalent in data science, ML, CS, mathematics, or 10 years of related work experience.
5+ years designing, implementing, and maintaining advanced AI systems and predictive models (supervised and unsupervised).
5+ years developing analytic rules and models using leading analytic tools and best practices.
5+ years developing regression, classification, and other statistical models to identify anomalies 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 Server and PostgreSQL.
2+ years developing and scaling natural language processing solutions.
2+ years presenting methods and findings to technical and non-technical stakeholders.

Responsibilities

Integrate and scale NLP methods to parse, clean, and analyze large corpora of unstructured text using OCR and LLMs as needed.
Design, develop, test, calibrate, and implement ML 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 analyzing large data sources.
Collaborate with investigators to determine analytic strategies while adhering to Rule 6(e) and privacy requirements.
Develop case leads for SBA OIG investigations from model outcomes.
Document all methodology, tests, and production models to evidentiary standards.
Build visualizations and dashboards conveying methodological choices, outcomes, and predictive capability.
Deliver findings in data summaries and executive-style reports for leadership.
Coordinate with the data engineering seat to support ML and text processing pipelines.
Create automation techniques using SharePoint, Python, Excel, Power BI, and Power Apps.