• Collect and validate required inputs, assumptions, and data from GAAP, Statutory, and Economic valuation processes to support scenario creation. • Set up and configure Moody’s scenario generation tools with appropriate assumptions and apply necessary updates. • Run scenario generation tools for defined scenarios and produce outputs in the required format for reporting and analysis. • Perform detailed checks, validations, and process controls to ensure scenario accuracy and compliance before review. • Maintain comprehensive process documentation, incorporating all latest changes and methodologies related to scenario creation. • Identify and implement improvements to enhance efficiency and accuracy in scenario generation and valuation processes.

• Provide advanced analytical leadership and expertise in the analysis and forecasting of financial, economic, and operational data to inform strategic and operational decisions • Establish, monitor, and refine key metrics to evaluate organizational performance and drive business intelligence • Deliver complex data analyses and insights to senior leaders, supporting executive decision-making • Evaluate industry, economic, financial, and market trends to forecast the organization's short, medium, and long-term financial and competitive position • Oversee end-to-end program evaluation, including ROI analysis, benchmarking, claims experience monitoring, and external vendor opportunity assessments • Identify actionable business opportunities and recommend solutions to enhance operational and financial performance • Collaborate with data science and cross-functional teams to develop and implement advanced analytical models and enhance analytic capabilities • Support strategic initiatives such as specialty and cost savings programs, value-based arrangements, and the development of advanced performance reporting and operational insights • Drive analytic strategy and develop innovative solutions to complex business problems, ensuring quality and compliance of actuarial deliverables • Serve as a senior resource for executive leadership, lead cross-functional initiatives, and mentor team members to build analytic capacity and consistency • Design, implement, and oversee robust processes and controls to ensure data management integrity and appropriate data flow across the enterprise • Proactively collaborate with key stakeholders—including executives and non-actuarial leaders—to understand business needs, troubleshoot systemic issues, and lead root cause analyses • Develop and implement cost-effective, strategic resolutions for data anomalies, ensuring alignment with organizational objectives • Advise executives on the development of enterprise and departmental strategies, exercising advanced independent judgment on highly complex technical and operational issues • Operate with minimal supervision, interpreting variable factors and determining optimal courses of action to drive change across functions

• Assist in managing the quality of the actuarial data warehouse • Prepare and analyze statistical models • Prepares statistics to consider various aspects before the Actuary suggests an insurance plan to the client • Support actuarial audits as well as external auditors during the audits • May train new actuarial staff • Provide details of financial transactions to the finance department

• Conduct modeling activities related to technical development and maintenance, pricing, regulatory reform, SAI support, process improvement, automation, documentation, and validation. • Take ownership of assigned components of Part D models; collaborate effectively and communicate clearly across teams. • Develop, enhance, and maintain robust Part D models and supporting processes. • Apply strong critical thinking to solve complex business problems. • Leverage advanced programming, Excel, and other tools to efficiently process and analyze large datasets. • Maintain clear and thorough documentation to support cross-training and alignment across models. • Create exhibits and narratives that effectively communicate insights and recommendations to both technical and non-technical audiences. • Implement process improvements through automation and process optimization. • Independently review work for accuracy and reasonableness; interpret and validate model results. • Respond to internal and external inquiries related to modeling outputs. • Communicate findings, insights, and recommendations clearly to a variety of stakeholders.