Lead Data Scientist, Actuarial & Advanced Risk Analytics (Healthcare)

Lead Data Scientist, Actuarial & Advanced Risk Analytics (Healthcare)

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets; an ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.

Please visit Fractal | Intelligence for Imagination for more information about Fractal.

Lead Actuarial & Risk Modeling Specialist – Data Science & AI (US Healthcare)

Employment Type: Contract

Note: This position is not eligible for Immigration Sponsorship at this time.

Role Summary

We are seeking a highly experienced actuarial and risk modeling specialist with deep expertise in the US healthcare system to play a foundational role in our Data Science and AI initiatives. This role will lead the design, development, and validation of actuarial, financial, and risk models that power predictive analytics, AI‑enabled decisioning, and enterprise risk insights across claims, members, providers, and populations.

The ideal candidate combines traditional actuarial rigor with modern data science and AI techniques and is comfortable translating complex healthcare risk dynamics into scalable, data‑driven models that drive measurable business and clinical outcomes.

This role is not a junior data science position—it requires proven leadership in actuarial modeling, healthcare risk analytics, and large‑scale healthcare datasets.

Key Responsibilities

Actuarial & Risk Model Development

• 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.

Healthcare Risk Analytics & AI Enablement

• 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.

Claims, Cost & Financial Risk Analysis

• 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.

Business & Stakeholder Leadership

• 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.

Required Skills & Experience

Core Actuarial & Risk Expertise

• 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.

Analytical & Technical Skills

• 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).

Business & Communication Skills

• 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.

Preferred Qualifications

• 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.

Domain: Healthcare Claims | Risk | Actuarial | Payment Integrity | Cost of Care

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.