VP, Advanced Analytics, Risk Adjustment

Kaiser Permanente is seeking a dynamic and visionary leader to serve as VP of Advanced Analytics. This role will lead National Health Plan Risk Adjustment analytics, benchmarking, encounter submission, and strategic analytic initiatives to support risk adjustment operations across multiple lines of business. The ideal candidate will bring deep healthcare risk adjustment expertise, a strong consulting background, and an actuarial designation is preferred (ASA or FSA), with a proven track record of leveraging complex data to influence medical group partners, national and functional leaders, and drive meaningful action through data-driven insights. This leader will also serve as an enterprise thought leader on evolving risk adjustment policy and methodology, interpreting CMS, HHS, and state regulatory developments to assess business and financial impact, guide strategic planning, inform executive decision-making, support predictive modeling and scenario analyses, and provide expertise to internal and external policy, advocacy, and stakeholder engagement efforts. This role demands strategic thinking, cross-functional collaboration, a commitment to innovation and quality, and the ability to build and inspire high-performing teams.

In this role, the VP of Advanced Analytics will build, lead, and inspire a multidisciplinary team of actuaries and advanced analytics professionals to generate actionable, decision-ready insights that directly support risk adjustment accuracy and value capture across all lines of business, including Medicare Advantage, ACA, and Medicaid. This leader will translate complex clinical, operational, financial, and regulatory information into practical strategies that improve documentation accuracy, strengthen prospective and retrospective risk adjustment programs, and enable consistent, compliant execution across regions. By partnering closely with clinical, operational, finance, care delivery, and policy stakeholders, this role will ensure analytics are embedded into workflows, support enterprise readiness for emerging risk adjustment methodologies, and drive measurable improvements in risk score integrity, quality outcomes, and financial sustainability across the organization.

This role will provide strategic analytics, benchmarking, and policy expertise to drive enterprise-wide performance, innovation, and compliance in support of Kaiser Permanentes National Health Plan Risk Adjustment organization.

• Strategic Analytics Leadership: Lead the development and execution of advanced analytics (i.e., define vision, data architecture, operating model, and success metrics) strategies that support risk adjustment operations across Medicare Advantage, ACA, and Medicaid. Utilize predictive modeling, machine learning, and statistical analyses to identify trends to drive optimal actions and outcomes, forecast risk scores, and optimize risk score accuracy capture. Ensure analytics initiatives are aligned with enterprise goals and regulatory requirements.
• Performance Management, Reporting, and Benchmarking: Design and maintain comprehensive benchmarking frameworks to evaluate internal performance against industry and peer organizations. Develop a comprehensive and robust data analytics strategy and performance management reporting suite (e.g., KPIs and dashboards) to ensure full transparency over risk adjustment reporting for all lines of business, inclusive of benchmarking against best practices and publicly available data.
• Encounter Submissions: This executive is accountable for accurate, timely, and compliant data submissions of the Medicare Advantage Encounter Data System (EDS) and HHS CMS EDGE server submissions. The role bridges health plan operations, data analytics, and regulatory compliance to maximize revenue accuracy and minimize financial risk by overseeing the ingestion, formatting and submissions, resolving data discrepancies, rejects, and anomalies to maximize submission acceptance rates. Partners with IT and vendors to maintain secure, scalable server infrastructure and provides executive-level dashboards tracking transfer payment estimates and data quality.
• Risk Stratification and Prospective Algorithms to Determine Patient Risk: Evaluate and implement analytical and predictive models (e.g., risk scoring, predicting gaps in care, forecasting, margin optimization, member segmentation) that directly support business goals such as margin improvement, support quality of care delivery, pricing strategy, value-based contracting, and regulatory compliance. This role will work collaboratively across the National Health Plan, Care Delivery, and the Permanente Medical Groups to align on both strategy and execution of that data to inform clinical, quality, and operational performance levers.
• Clinical Program Development and Quality Strategy: This role will leverage risk adjustment data and associated insights to inform clinical programs and quality strategies for use in complex care management, high-risk programs, and other 5-Star program elements. Data from this program will also inform care delivery strategies including community-based primary or supportive care, or other operating model considerations designed to improve access to care.
• Risk Adjustment Factor Forecasting: In partnership with national finance, actuarial, and other leaders, support the accurate development of Enterprise, product level risk adjustment forecasting for financial, clinical, and other product development and actuarial modeling such as the Medicare Advantage annual bid process and the ACA rate filings, among others.
• Thought Leadership: Collaborate with senior business stakeholders (e.g., payer/provider groups, finance, operations, strategy) to drive analytics adoption and ensure insights translate into actionable outcomes. Serve as a thought-leader within the organization: represent analytics in external forums, help set strategy for organizational data-driven transformation, mentor analytics talent.
• Team Leadership and Development: Build and lead a high-performing analytics team (data scientists, advanced statisticians, actuaries, business intelligence engineers), establish best practices in model governance, providing business with timely, accurate and actionable insights, and moving with speed.
• Regulatory Compliance: Establish strong data governance, ethics, model monitoring & validation processes, ensuring all analytics and benchmarking activities comply with CMS and state regulations, including HCC coding, RADV audits, and risk score submissions. Monitor regulatory changes and proactively adjust analytical methodologies to maintain compliance and optimize performance.