VP Health Services Analytics

Florida Blue•United States,

About The Position

The Vice President, Health Services Analytics is responsible for positioning the analytics functions as the engine behind the data-driven Health Services Operating System. This role refocuses existing analytics functions within Health Services on: implementing a Unified KPI & Operating Performance Dashboard, capturing automation/AI-driven efficiencies within the analytics functions, and identifying opportunities for business process improvement across Health Services Operations that drive improve member health outcomes, reduced administrative expense, reduced medical expense, and improve member experience. Reporting to the COO of Health Services, the VP, Health Services Analytics ensures that data, advanced analytics, and AI-powered insights are translated into measurable business outcomes. In partnership with the Chief Data Officer, this role ensures timely adoption of the Analytics Domain architecture within Health Services Analytics and leads the migration of Health Services analytical functions from legacy platforms to modern cloud-based solutions.

Requirements

Bachelor’s degree in actuarial science, Statistics, Mathematics, Data Science, Computer Science, Business, or a related quantitative field or additional related work experience.
15+ years of progressive experience in healthcare analytics, actuarial science, data science, or enterprise analytics leadership.
8+ years of senior leadership experience overseeing analytical teams and enterprise-scale initiatives.
Demonstrated experience designing and implementing analytics operating models.
Strong executive presence with the ability to influence cross-functional senior leadership.
Demonstrated ability to translate analytical insights into measurable business outcomes.

Nice To Haves

Fellow of the Society of Actuaries (F.S.A.) or equivalent advanced credential
Advanced degree (master’s or higher) in a quantitative or business discipline
Experience within a health insurance payer organization
Experience partnering with enterprise data organizations
Experience with process improvement methodologies (LEAN, Six Sigma, etc.)
Experience developing recruiting strategies, talent programs, and team members
Experience implementing AI-enabled analytics solutions into business workflows

Responsibilities

Define and own the North Star for Health Services Analytics as a distinct operating engine, articulating the future-state vision: what the analytics function must become, the capabilities it must build, and the proving metrics that demonstrate it is getting there.
Lead phased implementation of North Star vision: required capabilities, proving metrics, value drivers, organizational design, process maps, technology & data architecture, governance, strategic roadmap, maturity assessment, and management system.
Align the analytics engine's strategic priorities to that of the functions within Health Services Operations, with quantified business impact across STARS, RAF, quality, cost, and experience dimensions.
Establish and govern a unified analytics operating model with one intake process, one prioritization framework, one data product strategy, one governance model, one set of enterprise metrics, one transformation layer, and one AI enablement roadmap.
Implement an “Analytics Product Roadmap” for the analytics engine: articulate demand, prioritize, manage capacity, justify budget, and track value realization — partnering with Technology's "Front Door" to ensure demand visibility (volume, type, requestor, status) across all analytics requests.
Have representation in the operating rhythm governance forums for each operational engine, providing analytics inputs and ensuring decisions are data-informed.
Operate a disciplined management system for the analytics engine: weekly staff meetings, direct report 1:1s, skip-levels, quarterly roadmap revisions, and a structured operating rhythm.
Design, build, and maintain a comprehensive KPI inventory for Health Services Operations, including leading indicators, activity metrics, outcome metrics, benchmarks, targets, Red/Yellow/Green status reporting, and automated corrective action triggers.
Deliver the Unified KPI & Operating Performance Dashboard as the single source of truth for Health Services Operations, rolling into the enterprise Operating Performance Dashboard.
Build and own the standardized, governed transformation layer between enterprise data products and Health Services analytics products — encompassing metric definitions, transformation pipelines, business logic, enrichment layers, and quality checks — to eliminate duplicated pipelines, inconsistent outputs, and shadow data engineering.
In partnership with the Chief Data Officer, lead the migration of Health Services analytical functions from legacy platforms to modern cloud-based solutions, ensuring data arrives at the point of use ready to be consumed without requiring secondary engineering.
Shift the analytics engine's work mix from predominantly recurring reporting and ad hoc requests toward advanced analytics, predictive models, AI-enabled workflows, and proactive intelligence — and track that shift as a proving metric of the analytics engine's own maturity.
Develop and execute the AI enablement roadmap for Health Services Analytics, embedding predictive models and AI into the standardized transformation layer in alignment with Enterprise standards.
Identify and implement automation and AI-driven efficiencies within the analytics functions, including automated reporting, self-service dashboards, and decision-support tools.
Lead development of predictive models and AI/ML use cases identified in each operational engine's tactics table, ensuring alignment with the enterprise AI roadmap.
Own the analytics capability for TCOC connectivity across engines: define how analytics identifies affordability opportunities, the recurring reviews needed, the prioritization method, calendarization, and impact tracking/validation.
Maintain the connection between engine-level analytics and Medical Economics / Affordability, ensuring TCOC opportunities are quantified, tracked, and validated through recurring sustainable processes.
Support subfunction lever playbooks by identifying the KPI(s) each lever moves, the TCOC cost category and cost mechanism affected, and the analytics cadence required.
Build, lead, and develop the Health Services Analytics team, including analysts, analytics engineers, data scientists, and reporting specialists.
Define the staffing model for the analytics engine: FTE (filled/vacant), workforce mix, onshore/offshore/vendor split, and productivity expectations.
Upskill, restructure, and rebuild the analytics talent pyramid — shifting from a reporting-heavy workforce toward analytics engineers, data scientists, and AI-enabled roles — and track that shift as a proving metric of the engine's maturity.
Establish leadership development plans, talent assessments, and performance management systems for the analytics organization.

Benefits

Medical, dental, vision, life and global travel health insurance
Income protection benefits: life insurance, short- and long-term disability programs
Leave programs to support personal circumstances
Retirement Savings Plan including employer match
Paid time off, volunteer time off, 10 holidays and 2 well-being days
Additional voluntary benefits available
A comprehensive wellness program
Competitive pay
Opportunities for incentive or commission compensation
Regular annual reviews with pay for performance considerations for base pay increases