Data Scientist
Core
Develop fraud detection and actuarial decision-support models using health insurance data to support pricing, underwriting, and claims analytics.
Role type
Data Scientist (Fraud Detection & Actuarial Analytics)
Builds
Production ML models for fraud/abuse detection, predictive risk models, and AI-assisted analytical tools
Domain
Health Insurance / Actuarial Science / Fraud Detection
Deliverable
production ML models
Required skills
Python, SQL, Statistics, Machine Learning, Anomaly Detection, Feature Engineering, Model Deployment, Data Visualization
Preferred skills
LLMs, AI Agents, Graph Analytics, Oracle/PLSQL, Cloud Platforms, Docker, CI/CD
Technologies
Python, Pandas, NumPy, Scikit-learn, SQL, Oracle, OCI, Docker, FastAPI, Git
Responsibilities
Develop and validate FWA detection models (provider profiling, outlier detection, network analysis); Build predictive models for pricing and underwriting; Deploy models to production and monitor performance; Translate findings into BI dashboard features and KPIs; Prototype LLM and agent-based capabilities; Collaborate with cross-functional teams to deliver analytical solutions.
Seniority
Mid-Senior, hands-on IC
