Medicaid Risk Adjustment Analytics Leader

Hispanic Alliance for Career Enhancement

Illinois

Hybrid

USD 100,000 - 231,540

Full time

14 days+

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Benefits offered by this job

Bonus eligibility

Equity awards

Comprehensive benefits

Job summary

CVS Health is seeking a Lead Director for Revenue Integrity Informatics (Medicaid) to provide strategic leadership for Medicaid risk adjustment analytics, reporting, and informatics within a dynamic risk adjustment team. The role oversees data pipelines, risk score integrity, and program insights across markets, driving compliant revenue capture and performance improvement.

The position requires 10+ years in healthcare analytics, 3+ years of leadership, and advanced SAS/SQL/Python skills, with

Qualifications

10+ years of experience in healthcare analytics and reporting, risk adjustment including relevant working knowledge with claims.
3+ years of leadership experience including people managing, coaching, or mentoring team members.
Advanced technical skills in SAS, SQL, Python, or cloud-based analytics platforms (e.g. BigQuery, Snowflake, Databricks, or similar).
Expertise in state and regulatory requirements, risk adjustment methodologies, and encounter data processes.
Strong knowledge of risk models (e.g., CDPS, CRG, HCC) and state reconciliation processes.
Proven ability to develop and execute strategic initiatives that deliver measurable business outcomes.
Demonstrated leadership experience managing cross-functional teams and large-scale programs.
Experience with data visualization tools (e.g. Tableau, Power BI, QuickSight, Looker, etc.).

Responsibilities

Define and execute Medicaid risk adjustment strategy across markets and plans.
Lead and deliver high-impact strategic initiatives that improve revenue accuracy, compliance, and overall performance.
Align risk adjustment programs with state Medicaid models (e.g., CDPS, CRG, or state-specific methodologies).
Represent risk adjustment Medicaid informatics in executive forums to drive alignment on strategic goals and translate analytics into actionable financial and operational strategies.
Oversee health plan performance using advanced analytics and use proactive data insights to drive strategies and evidence-based decision-making.
Lead development of scalable data pipelines and reporting frameworks using claims, encounters, pharmacy, and clinical data.
Lead advanced analytics for risk score development, predictive modeling, forecasting, trend analysis, and opportunity identification.
Ensure accuracy, integrity and completeness of Medicaid encounter submissions and data.
Defines data analysis methodologies, subsequently driving predictive and prescriptive analytics projects and communicating insights to key stakeholders.
Establish and oversee processes to ensure accuracy, completeness, and integrity of risk capture.
Lead reconciliation of plan-calculated risk scores to state-reported scores, including variance analysis and root cause identification.
Monitor and validate encounter data submissions and their downstream impact on state risk scoring and payments.
Partner with actuarial and finance teams to ensure alignment between risk scores, revenue projections, and state payments.
Ensure readiness for state audits and external reviews through robust data validation and documentation practices.
Stay current on evolving Medicaid policies, state methodologies, and reporting requirements.
Direct suspecting logic development, gap identification, and prioritization strategies for operational programs and interventions.
Measure and evaluate program performance and locate opportunities for expansion, improvement, or savings.
Establish program KPIs to monitor intervention effectiveness.
Partner with clinical operations and vendor teams to ensure alignment with state requirements.
Align data strategies with value-based initiatives and provider-level drilldowns for consistent performance management across markets.
Lead and develop a high-performing, multidisciplinary team spanning informatics, risk analytics, reporting, and operational program support.
Define a clear organizational structure, aligning roles across strategy, analytics, and process execution to ensure end-to-end accountability.
Establish governance frameworks for prioritization and execution of risk adjustment initiatives, ensuring alignment with enterprise goals, market needs, and regulatory timelines.
Drive integration across analytics and operations, ensuring that insights are translated into actionable intervention programs and measurable outcomes.
Develop talent strategy including coaching and mentorship of advanced analytics, Medicaid risk models, and leadership capabilities.
Foster a culture of data integrity, accountability, and continuous improvement optimization of workflows and analytic methodologies.
Ensure scalability and sustainability of operations by standardizing tools, reporting, and processes across markets.
Leverage automation and data infrastructure improvements to reduce manual effort and increase speed to insight.