Senior Data Scientist

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.

Qualifications

• One Of The Following 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.