• Align with business, clinical, and technology stakeholders on analytics strategies • Assist the EM/AP to develop contracts, statement of work (SOW), targeted proposals • Manage the intake of such initiatives & client requests and assist the EM/AP to develop proposals • Provide information and data analytics for and report to the EM or research leader • Work with Senior Vice President (SVP), Business Development to assist with sales calls • Prepare and coordinate the necessary materials for each client meeting • Develop, coordinate, and organize business and meeting schedules for BD team members

• Designing and enhancing risk-based analytic models to identify high-risk providers, services, and utilization pattern • Conducting exploratory and targeted data analyses to support CMS program integrity initiatives • Supporting development of dashboards, visualizations, and reporting products for CMS leadership and technical staff • Collaborating with the prime contractor and CMS to refine analytic methodologies, assumptions, and outputs • Translating analytic results into clear findings, documentation, and recommendations usable by non-technical audiences

• Lead complex analytics initiatives requiring advanced scripting and analytical methods. • Design, build, and maintain analytical solutions using SQL, Python, and R. • Contribute across the full analytics lifecycle: discovery, design, development, validation, and refinement. • Define and enforce enterprise-wide analytics and coding standards, including governance of citizen-developed solutions. • Conduct code reviews to ensure quality, performance, maintainability, and alignment with standards. • Develop reusable Python and R packages, shared SQL patterns, and analytical frameworks. • Support business partners with advanced analytical needs beyond standard BI reporting. • Apply advanced statistical and analytical techniques to solve complex business problems. • Selectively apply AI/ML techniques where they deliver clear business value. • Collaborate with Data Engineers and Architects to ensure alignment with data models, pipelines, and governance. • Clearly communicate insights, tradeoffs, and recommendations to technical and non-technical stakeholders. • Stay current with emerging analytics technologies and assess applicability.

• Develop end-to-end AI solutions, from discovery through deployment and monitoring, including modeling (NLP/ML/LLMs), APIs, and integrations. • Design and evolve chatbots and conversational channels using NLP/NLU, driving continuous improvement. • Build integrations via APIs/JSON, microservices, and event-driven architectures, and implement MLOps with pipelines, versioning, and observability. • Analyze conversational data and recommend actions based on KPIs, ensuring quality through testing and validation. • Work in agile methodologies, collaborating with business, design, engineering, and security teams.