Senior Actuary, Health Plan Analytics
Reveleer
Senior Actuary, Health Plan Analytics
Reveleer delivers a unified platform spanning risk adjustment, quality improvement, clinical intelligence, and member management for health plans and provider organizations navigating the complexity of value-based care. Trusted by 80+ customer organizations nationwide, the platform integrates data, analytics, and intelligent workflow automation into one governed system designed to support traceable documentation across diagnoses, quality measures, and submissions. With regulatory expertise and transparent, human-in-the-loop AI at its core, Reveleer supports organizations working to advance care quality, strengthen documentation integrity, and sustain the operational readiness needed to navigate audits with confidence.
Reveleer is hiring a senior actuary to lead health plan and risk adjustment analytics for each line of business for Reveleer customers across Medicare Advantage (MA), Medicare Advantage Prescription Drug (MAPD), Affordable Care Act (ACA), Medicaid, and provider value-based contracts. This role builds member-level actuarial models that quantify risk adjustment performance, HCC (Hierarchical Condition Category) capture, medical economics, utilization, and population health trends, and translates those models into customer-facing dashboards that inform pricing, forecasting, and program strategy.
This actuary works directly with customer success, analytics, product, operations, and clinical teams to convert raw claims, encounter, member, provider, and clinical data into decision-ready outputs. The role requires both technical model-building skill and the ability to explain actuarial and risk adjustment concepts to non-actuarial stakeholders, including provider and health plan executives.
What You Will Do
- Build and maintain member-level actuarial models covering risk adjustment performance, HCC capture and recapture, medical economics, utilization patterns, and population health metrics across MA, MAPD, ACA, and Medicaid populations.
- Develop analytics that can support rate-setting for Medicare Advantage Bids, ACA rate filings, Medicaid capitation arrangements, and value-based contract terms.
- Reconcile RAF calculations against source files, including the Monthly Membership Report (MMR), Model Output Report (MOR), MAO-004, and the Beneficiary-Level file, and extend that reconciliation logic into customer-facing reporting.
- Design the actuarial and analytic logic behind customer-facing dashboards, partnering with data engineering and product teams to translate member-level models into usable, accurate, and timely visualizations.
- Produce forecasting and accrual models that support midyear and final settlement estimates, transfer payments, capital planning, and financial reporting for risk adjustment programs.
- Analyze utilization trends, medical loss ratio (MLR) drivers, and cost-of-care patterns to identify actionable opportunities for customers managing value-based contracts.
- Support MA and HHS RADV (Risk Adjustment Data Validation) readiness by modeling audit exposure and prioritizing chart review and coding efforts based on financial impact.
- Communicate model methodology, assumptions, and results clearly to actuarial and non-actuarial audiences, including customer executives.
- Partner with clinical, coding, retrieval, and provider engagement teams to align analytic outputs with chronic HCC recapture, care gap closure, and quality initiatives.
What You Bring
Required qualifications
- Seven or more years of actuarial or actuarial-adjacent analytics experience in health plan pricing, risk adjustment, or medical economics.
- Direct pricing or performance modeling experience across at least three of the following: Medicare Advantage, MAPD, ACA, Medicaid, and value-based contracts.
- Working knowledge of the CMS-HCC and ACA risk model, RAF score calculation, and the relationship between ICD-10 diagnosis coding and risk adjustment revenue.
- Demonstrated experience building member-level data models that feed reporting or dashboard tools, such as Tableau or Power BI.
- Proficiency in SQL and at least one statistical or scripting language, such as SAS, R, or Python.
- Proficiency in utilizing AI tools to support modeling
- Bachelor's degree in actuarial science, mathematics, statistics, economics, or a related quantitative field.
- Strong written and verbal communication skills, with experience presenting actuarial findings to executive audiences.
Preferred qualifications
- Associate of the Society of Actuaries (ASA) designation or Fellowship (FSA) or progress toward.
- Experience with CMS files, including the MMR, MOR, MAO-004, and Beneficiary-Level file.
- Experience with EDPS & EDGE encounter submissions and encounter data quality processes.
- Prior experience supporting RADV & IVA audit readiness or chart review prioritization.
- Familiarity with provider incentive program design tied to chronic HCC recapture or quality performance.
- Experience with financial forecasting, including ACA transfer payments and MA settlement accruals
Tools and technical skills
SAS (Enterprise Guide), SQL, Tableau, Microsoft Excel, R and RStudio, Python, Microsoft Access, and Microsoft Visual Basic (VBA) are all relevant to this role. Reveleer does not require proficiency in every tool listed; candidates should be strong in at least three of these and comfortable learning the rest on the job.
What You'll Receive:
- Competitive salary
- Medical, Dental and Vision benefits
- 401k match
- Generous PTO plan
- Our compensation reflects the cost of labor across several US geographic markets. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.
- Reveleer E-Verifies all new hires.
- Reveleer is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, disability status or genetic information, in compliance with applicable federal, state and local law.
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