The Senior Data Scientist provides advanced analytics, machine learning, and investigative data support. Working closely with criminal investigators, auditors, and technical stakeholders, this position develops and maintains predictive models, fraud detection methodologies, natural language processing (NLP) solutions, and analytical products designed to identify financial fraud, improper payments, and program noncompliance. The Senior Data Scientist transforms complex datasets into actionable intelligence by applying statistical, machine learning, and data visualization techniques.

• Design, develop, test, calibrate, and deploy advanced machine learning and predictive analytics models.
• Develop and maintain supervised and unsupervised fraud detection methodologies using regression, classification, clustering, Bayesian, and ensemble techniques.
• Conduct data quality assessments to identify anomalies, inconsistencies, and data integrity issues.
• Analyze large structured, semi-structured, and unstructured datasets to identify fraud indicators and investigative leads.
• Collaborate with criminal investigators to support financial fraud investigations and audits.
• Integrate NLP, OCR, semantic similarity algorithms, and large language models into analytical workflows.
• Develop visualizations, dashboards, executive summaries, and analytical reports for technical and non-technical audiences.
• Document methodologies, models, testing procedures, and analytical results in accordance with evidentiary and federal requirements.
• Coordinate with Data Engineering personnel to ensure system architecture efficiently supports analytical and machine learning requirements.
• Create automated analytical solutions using Python, Power BI, SharePoint, Excel, Power Apps, and related technologies.

• Current clearance or ability to obtain a public trust clearance.
• Master's degree, Ph.D., or equivalent doctorate-level degree in Data Science, Machine Learning, Computer Science, Mathematics, or related field; or 10 years of relevant applied experience.
• Five or more years of experience developing advanced AI systems and predictive analytics models.
• Five or more years of experience applying modern analytic methodologies and statistical modeling techniques.
• Three or more years supporting financial fraud investigations or government oversight activities.
• Three or more years working with Python and Pandas for advanced data analysis.
• Three or more years working within cloud platforms such as Microsoft Azure, AWS, or GCP.
• Two or more years of advanced SQL development experience.
• Two or more years developing and deploying NLP solutions.