• Design, develop, and deploy predictive and analytical models using advanced data science techniques to extract insights from complex healthcare data • Collaborate with clinical experts and researchers to generate actionable predictions and deliver evidence-based recommendations that improve revenue cycle outcomes • Utilize cloud platforms to build scalable data analytics pipelines and AI models • Collaborate with cross-functional teams to integrate AI/ML models into existing solutions and workflows • Effectively communicate complex findings to key stakeholders

• Build scalable solutions • Work with large volumes of data • Participate in strategic projects involving Data Platforms, Cloud, and AI

• Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives. • Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights. • Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy. • Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization. • Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise. • Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward. • Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.

• Help teach our AIs to think • Dive into data and discover patterns • Train models and create decision logic • Implement LangChain and build autonomous agents • Support the end-to-end lifecycle of a Data Science project