Senior Data Scientist - Public Healthcare Fraud Detection - Remote

Overview

The Senior Data Scientist handles advanced analytics, AI/ML modeling, and large-scale data integration to lead the development of fraud detection models for federally funded public healthcare programs to include statistical research, policy, and cutting-edge technology to detect, quantify, and mitigate fraud.

In Short

• Lead the design, development, and implementation of advanced fraud detection and risk-scoring algorithms leveraging AI, machine learning, and explainable AI techniques.
• Architect and oversee secure data pipelines to integrate, clean, and standardize heterogeneous datasets.
• Apply deterministic and probabilistic record linkage methods within a secure environment.
• Conduct literature reviews to identify and adapt fraud taxonomies, definitions, measures, and behavioral indicators.
• Collaborate closely with stakeholders and other agencies.
• Develop analytical workflows for unstructured data preparation and anomaly detection.
• Deliver reproducible, open-source analytical outputs including datasets and documentation.
• Translate analytical findings into actionable insights for technical and policy audiences.
• Provide technical leadership and mentorship to multidisciplinary project teams.

Requirements

• Experience in data science and analytics.
• Strong knowledge of AI and machine learning techniques.
• Proficiency in data integration and data pipeline architecture.
• Experience with statistical research and fraud detection methodologies.
• Ability to collaborate with diverse stakeholders.
• Strong communication skills for technical and policy audiences.
• Experience in agile project management practices.

Benefits

• Flexible working hours.
• Opportunities for professional development.
• Collaborative work culture.
• Recognition for contributions.
• Access to large company perks with a small company feel.