Senior Data Scientist

Ardent Eagle Solutions•Arlington, VA

5d•Remote

About The Position

Ardent Eagle Solutions (AES) is seeking an experienced Senior Data Scientist to support the Small Business Administration (SBA), Office of Inspector General (OIG), Technology Solutions Division. This position supports advanced analytics initiatives focused on fraud detection, investigations, predictive modeling, and artificial intelligence solutions. The successful candidate will develop sophisticated machine learning models, leverage natural language processing (NLP), collaborate with investigators, and deliver actionable insights that strengthen oversight of SBA programs. The Office of the Inspector General (OIG) is an independent and objective oversight office created by the Inspector General Act of 1978, as amended. The Small Business Administration (SBA) OIG provides auditing, investigative, and other oversight services to support and assist SBA in achieving its statutory mission to maintain and strengthen the Nation’s economy by protecting the interests of and assisting small businesses and helping families and businesses to recover from disasters. OIG utilizes large volumes of data to perform its auditing and investigative mission sourced from within SBA, other federal agencies, and the private sector. To facilitate the work of OIG audits and investigations, OIG has created the Technology Solutions Division (TSD).

Requirements

Master's degree (or higher) in Data Science, Computer Science, Machine Learning, Mathematics, Statistics, or a related discipline; OR Ten (10) years of directly applicable professional experience.
Five (5)+ years designing, developing, and maintaining advanced AI systems and predictive analytics models.
Five (5)+ years developing fraud detection models utilizing modern analytical techniques.
Five (5)+ years developing statistical models including regression, classification, clustering, and anomaly detection.
Three (3)+ years supporting fraud, abuse, or criminal investigations through advanced analytics.
Three (3)+ years utilizing Python (Pandas required).
Three (3)+ years working within cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
Two (2)+ years performing advanced SQL development using SQL Server and PostgreSQL.
Two (2)+ years developing Natural Language Processing (NLP) solutions.
Two (2)+ years presenting technical findings through reports, dashboards, briefings, and visualizations.
Public Trust eligibility and U.S. Citizenship are required.

Nice To Haves

Experience supporting Offices of Inspector General, federal law enforcement, or investigative organizations.
Experience developing fraud detection algorithms.
Experience with Azure Machine Learning.
Experience utilizing OCR technologies and Large Language Models.
Experience with Power BI visualization development.
Experience handling large-scale structured and unstructured datasets.
Master's degree or higher in Data Science, Computer Science, Machine Learning, Mathematics, Statistics, or a closely related technical discipline preferred.
Certifications: Microsoft Certified: Azure AI Engineer Associate, Microsoft Certified: Azure Data Scientist Associate, Microsoft Certified: Azure Fundamentals.

Responsibilities

Design, develop, implement, and maintain advanced machine learning models utilizing supervised and unsupervised learning techniques.
Build predictive analytics solutions to identify fraud, improper payments, waste, abuse, and non-compliance across SBA programs.
Develop regression, classification, clustering, Bayesian, ensemble, and anomaly detection models.
Perform data quality assessments to evaluate completeness, consistency, and validity of source data.
Develop repeatable methodologies for efficiently analyzing large structured, semi-structured, and unstructured datasets.
Collaborate directly with criminal investigators to support active investigations while maintaining compliance with federal evidentiary requirements and protected information handling.
Develop and scale Natural Language Processing (NLP) solutions utilizing OCR, semantic similarity algorithms, large language models (LLMs), and related technologies.
Coordinate with Data Engineers to ensure cloud architecture effectively supports machine learning workloads.
Produce technical documentation supporting analytical methodologies, model development, testing, validation, and production implementation.
Develop dashboards, reports, executive briefings, and visualizations using Power BI and other reporting platforms.
Present analytical findings to both technical and executive audiences.
Develop automation solutions utilizing Python, SharePoint, Microsoft Excel, Power BI, and related technologies.
Identify emerging analytical opportunities that improve fraud detection, investigative effectiveness, and organizational reporting.
Support continuous improvement of analytics capabilities and emerging AI technologies.