Sr. Data Scientist

Summary

Build fraud-detection models and analytics workflows using SAS Viya to identify waste, abuse, and anomalies in health-insurance data.

Develop predictive models and statistical algorithms for Fraud, Waste, and Abuse (FWA) detection using SAS Viya and traditional SAS tools.
Perform machine learning and AI-based anomaly detection leveraging Viya’s cloud-native capabilities.
Design and implement analytics workflows on SAS Viya, including data preparation, model training, and deployment.
Optimize Viya environments for scalability and performance in on-prem and cloud setups.
Manage large health insurance datasets across Viya and SAS platforms ensuring data integrity and compliance.
Integrate Viya with other systems for seamless data flow and governance.
Work with business teams to define FWA strategies and KPIs.
Partner with IT for Viya infrastructure setup and cloud migration.
Build interactive dashboards and reports using Viya’s visualization tools.
Present insights and recommendations to stakeholders for fraud prevention.

Bachelor’s or Master’s in Data Science, Statistics, Computer Science, or related field.
Strong proficiency in SAS Viya and SAS Base/Enterprise Guide.
Experience with machine learning, AI, and statistical modeling on Viya.
Knowledge of Python/R integration with SAS Viya and SQL.
Experience in health insurance analytics and FWA detection is highly desirable.
Familiarity with cloud platforms (Azure, AWS) and Viya’s Kubernetes‑based architecture.
Strong analytical, problem‑solving, and communication skills.