[Remote] Lead Actuarial & Risk Modeling Specialist – Data Science & AI (US Healthcare)
Note: The job is a remote job and is open to candidates in USA. Fractal Analytics is a strategic AI partner to Fortune 500 companies, aiming to power every human decision in the enterprise. They are seeking a highly experienced actuarial and risk modeling specialist to lead the design and development of models that drive predictive analytics and AI-enabled decision making in the US healthcare system.
Responsibilities
- Design, build, and enhance actuarial models related to medical cost forecasting, utilization risk, trend analysis, and financial projection
- Develop risk adjustment, severity, and morbidity models for Medicare, Medicaid, and Commercial populations
- Lead modeling efforts for cost-of-care, member risk stratification, high-cost claimant prediction, and population health risk scoring
- Apply proven actuarial methodologies while incorporating advanced statistical and machine learning techniques where appropriate
- Partner with Data Science and AI teams to translate actuarial models into scalable analytical and AI solutions
- Evaluate and guide the use of ML approaches (GLMs, GAMs, gradient boosting, survival analysis, time series, etc.) alongside actuarial methods
- Ensure explainability, stability, and regulatory readiness of risk models used in AI-driven workflows
- Support development of predictive and prescriptive analytics used in Payment Integrity, care management, utilization management, and financial risk mitigation
- Perform deep analysis across claims, member, and provider datasets to identify cost drivers, risk concentration, and leakage
- Quantify financial impact of payment programs, adjudication rules, benefit design, and provider behavior
- Support Payment Integrity (PI) use cases including duplicate claims, pricing anomalies, eligibility issues, and reimbursement accuracy
- Partner with finance and actuarial teams on budgeting, reserving, and forecasting exercises
- Act as a domain authority for actuarial and healthcare risk concepts within data science and AI initiatives
- Translate complex analytical results into clear, executive-ready insights and recommendations
- Guide analysts and data scientists on actuarial standards, modeling assumptions, and validation techniques
- Support regulatory, audit, and compliance reviews through transparent documentation and defensible methodologies
Skills
- 10+ years of experience developing actuarial, risk, or financial models in the US healthcare industry
- Strong background in one or more segments: Medicare (MA, FFS, Risk Adjustment), Medicaid / State programs, Commercial / Employer plans
- Proven experience with cost modeling, utilization forecasting, trend analysis, and member risk stratification
- Deep understanding of claims adjudication, benefit design, pricing, and reimbursement mechanics
- Advanced statistical modeling expertise (GLMs, regression, survival models, time series)
- Strong hands-on experience with analytical tools and languages (Python, R, SQL, or similar)
- Ability to work with large, complex healthcare datasets (claims, eligibility, provider, utilization)
- Experience collaborating with data science teams using modern analytics platforms (Databricks or similar preferred)
- Exceptional analytical thinking and problem-solving ability
- Strong communication skills with the ability to explain complex actuarial concepts to technical and non-technical audiences
- Demonstrated ability to influence decisions at senior leadership levels
- Actuarial credentials (ASA, FSA) or significant progress toward certification
- Experience supporting AI, advanced analytics, or digital transformation initiatives
- Exposure to Payment Integrity, FWA analytics, care management, or utilization management programs
- Experience with forecasting dashboards, scenario modeling, or executive financial reporting
- Familiarity with Call Center datasets (member & provider interactions), Provider RCM data, and/or EHR/clinical data for integrated risk analysis
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