• Develop and deploy scalable machine learning and AI solutions in production environments, ensuring performance and sustainability • Build and refine models for customer segmentation, risk prediction, clinical decision support, and other healthcare-specific use cases • Ensure rigorous use of statistical methods, reproducibility, and documentation across all projects • Design and implement statistical tests, A/B experiments, and performance monitoring strategies • Evaluate ML/AI models and products for fairness in output, targeting and actions • Partner with stakeholders to define problem statements, identify data sources, and design effective solutions • Build and maintain robust data pipelines, modeling workflows, and monitoring tools in collaboration with engineering and data platform teams • Partner with senior and executive leadership to define and advance the enterprise AI roadmap, identifying high-impact opportunities to embed ML and AI services into core business workflows • Lead multiple high-impact data science projects across areas including Clinical, STARs, Risk Adjustment, Claims, Pharmacy, Marketing and Member Experiences • Manage and mentor a team of data scientists; provide technical guidance via review of code, models, and analytical approaches; foster professional growth; and drive a culture of experimentation and continuous learning