Lead Analyst, National Risk Adjustment Predictive Analytics

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Analyst, National Risk Adjustment Predictive Analytics based in United States.

This role offers the opportunity to lead advanced analytics supporting enterprise-wide healthcare risk adjustment strategies.

You will transform complex claims, pharmacy, laboratory, financial, and utilization data into actionable insights.

The position plays a key role in developing predictive models, targeting engines, tracking systems, and automated reporting solutions.

You will help measure intervention outcomes, identify trends and anomalies, and forecast future performance across multiple lines of business.

Working in a fast-paced, agile environment, you will partner with business leaders and cross-functional stakeholders to solve complex analytical challenges.

Your work will directly support strategic decisions across Medicaid, Marketplace, Medicare, and Medicare-Medicaid programs.

This is an opportunity for an experienced healthcare analytics professional to combine technical leadership, statistical analysis, and business impact.

Accountabilities:

• Lead analytical support for prospective and retrospective risk adjustment intervention strategies, including tracking progress, outcomes, and financial or operational impact.
• Design and develop systems to track risk scores, intervention outcomes, market performance, and results across multiple lines of business.
• Develop automated and ad-hoc quality assurance reporting modules supporting Medicaid, Marketplace, Medicare, and Medicare-Medicaid programs.
• Support the development of automated suspect, targeting, and ranking engines to identify opportunities for risk adjustment interventions.
• Analyze complex healthcare datasets, including claims, pharmacy, laboratory, utilization, financial, and performance data, using data mining, validation, scrubbing, and root-cause analysis techniques.
• Identify anomalies, outliers, changing trends, and improvement opportunities using statistical methodologies, and translate findings into concise executive-level recommendations.
• Apply extrapolation, interpolation, forecasting, and other analytical techniques to predict trends in cost, utilization, risk scores, and performance.
• Partner with cross-functional stakeholders and leaders to define business requirements, clarify data needs, communicate findings, and escalate issues when appropriate.
• Conduct preliminary and post-implementation impact analyses for changes to analytics logic, source code, reporting modules, and data warehouse platforms.
• Manage changes and upgrades to data warehouse and analytics environments while maintaining continuity and transparency for end users.
• Support special projects requested by internal teams, regulatory bodies, contracting organizations, and other external stakeholders.
• Monitor applicable CMS and state risk adjustment regulations, incorporate regulatory changes into analytics activities, and provide training and education as needed.
• Develop training materials and deliver guidance to help analysts understand analytical processes, solutions, and reporting designs.
• Train new and existing team members while promoting a collaborative, agile, and continuous-improvement culture.

Requirements

• Minimum of 4 years of experience developing complex SQL queries, functions, procedures, and data designs within relational database environments.
• Hands-on experience with Microsoft T-SQL, Databricks SQL, Power BI, SQL Server Integration Services (SSIS), and SQL Server Reporting Services (SSRS).
• Experience applying predictive modeling, statistical analysis, forecasting, and performance tracking techniques within healthcare, quality, HEDIS, risk adjustment, finance, or health plan environments.
• Demonstrated ability to work with complex datasets and quantify financial, utilization, operational, and performance metrics.
• Experience with cloud or distributed data platforms such as Microsoft Azure, Amazon Web Services (AWS), or Hadoop.
• Strong analytical thinking, attention to detail, problem-solving ability, and experience performing structured root-cause analysis.
• Strong business acumen with the ability to connect analytical findings to broader strategic and operational objectives.
• Excellent communication skills, including the ability to explain complex technical and analytical concepts to non-technical stakeholders and executives.
• Proven ability to lead cross-functional initiatives and deliver measurable results within highly matrixed organizations.
• Ability to manage multiple priorities and meet demanding deadlines in a fast-paced, agile environment.
• Self-directed approach, strong ownership, adaptability, and a continuous-improvement mindset.
• Strong written and verbal communication skills and proficiency with Microsoft Office applications.
• Familiarity with Python and R programming or broader data science techniques is preferred.

Benefits

• Competitive annual salary range of $72,370.82-$156,803.45, with actual compensation dependent on factors such as geographic location, experience, education, and skill level.
• Comprehensive benefits and compensation package.
• Full-time employment with a U.S.-based opportunity.
• Opportunity to work on enterprise-scale healthcare analytics spanning multiple lines of business.
• Exposure to advanced predictive analytics, risk adjustment, forecasting, data engineering, and business intelligence initiatives.
• Collaboration with cross-functional healthcare, analytics, finance, quality, and business teams.
• Professional development through training, knowledge sharing, and opportunities to contribute to strategic analytical projects.