Analyze and manipulate claims data to support payment integrity and medical cost savings initiatives. Collaborate with claims analysts, ideators, and cross-functional data teams to identify savings opportunities, research data, troubleshoot anomalies, and ensure analytical accuracy. The role requires claims analysis experience, SQL and advanced Excel skills, and strong analytical capabilities. Python, data engineering, Snowsight, and claims platforms are preferred.

Leads advanced data science and machine learning initiatives to discover healthcare affordability and payment integrity opportunities. Develops anomaly detection, clustering, graph analytics, explainable AI, generative AI, and evidence-generation methods using large-scale healthcare data. Partners with product, engineering, analytics, and domain stakeholders to translate patterns into actionable hypotheses, operationalize analytical assets, and improve model validation. Provides technical leadership, establishes analytical standards, mentors data scientists, and guides ambiguous initiatives from problem definition through delivery.

Provides technical leadership for a portfolio of modernized enterprise applications. Establishes architecture and engineering standards, guides design and implementation, manages technical risks and dependencies, improves testing and delivery practices, and supports production readiness. The role partners with product, architecture, security, infrastructure, and business stakeholders while mentoring engineers and remaining hands-on with critical code and complex technical issues. It also establishes governance for AI-assisted software development.