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EY is a global professional services firm offering audit, tax, consulting, and advisory expertise. Its teams help organizations address complex business challenges, strengthen trust in financial reporting and markets, and use data and technology to support transformation.

The firm provides services including corporate finance advisory, transaction strategy, and technology consulting. EY works with clients across areas such as healthcare, legal services, marketing, energy, finance, and government, with sustainability and innovation informing many of its solutions.

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EY Risk Consulting Manager – Actuarial Healthcare Analytics and Model Validation

EY seeks a manager to validate healthcare cost, claims, predictive, and AI/ML models. The role leads analytics engagements for insurance-sector clients through EY’s global delivery services.

INIndiaOn-siteFull-timeSeniorLeadEnglish RequiredActuary
CloudPythonSQLVBA

Description

  • Deliver actuarial and analytics solutions for insurance-sector clients
  • Collaborate with staff, consultants, managers, client partners, and global insurance and consulting professionals
  • Conduct independent validation and model risk management for financial, operational, predictive, forecasting, and AI/ML models
  • Evaluate model methodologies, assumptions, data quality, performance, documentation, and governance frameworks
  • Deliver high-quality results and practical solutions with engagement teams
  • Provide targeted solutions and training for staff and senior team members
  • Complete engagements within assigned timelines and quality standards
  • Set team priorities, report progress and risks, and monitor margins and resource utilization
  • Partner with client teams, data scientists, business users, and EY professionals
  • Validate healthcare cost forecasting and claims prediction models
  • Review claims cost and utilization forecasting methodologies
  • Assess budget planning and financial forecasting models
  • Evaluate reimbursement optimization and revenue cycle analytics models
  • Review Fraud, Waste and Abuse detection models and analytical frameworks
  • Support validation of AI/ML models used in healthcare decision-making
  • Analyze large healthcare datasets for trends, anomalies, and model performance issues
  • Conduct ad hoc analytical projects and research
  • Keep current with healthcare analytics, predictive modeling, AI/ML, model governance, and relevant business and economic developments

Requirements

  • At least 7 years of experience in healthcare analytics, predictive modeling, model validation, actuarial analytics, risk analytics, data science, or a related quantitative field
  • Bachelor’s or master’s degree in statistics, mathematics, actuarial science, data science, economics, engineering, computer science, or a related quantitative discipline
  • Strong knowledge of statistical, forecasting, predictive modeling, and machine learning techniques
  • Advanced Microsoft Excel skills, including PivotTables, Power Query, advanced formulas, data modeling, data validation, and VBA/macros
  • Strong analytical and problem-solving skills
  • Ability to manage multiple tasks with a flexible approach to work
  • Ability to interpret complex quantitative results and communicate conclusions clearly
  • Experience managing teams and delivering projects
  • Experience in US healthcare, health insurance, or managed care organizations preferred
  • Exposure to healthcare claims analytics, medical cost forecasting, utilization management, or provider analytics preferred
  • Experience reviewing AI/ML models and predictive analytics solutions preferred
  • Familiarity with model risk management frameworks and governance standards preferred
  • Knowledge of Medicare, Medicaid, commercial health insurance, and provider reimbursement processes preferred
  • Experience presenting analytical findings and validation conclusions to senior stakeholders preferred
  • Exposure to cloud analytics platforms and modern data ecosystems preferred
  • Strong SQL skills and experience working with large datasets preferred
  • Experience using Python and/or SAS for analytics, model development, or validation preferred
  • Experience conducting data quality reviews and quantitative testing preferred
  • Knowledge of GenAI and Agentic AI is advantageous

Benefits

  • Ongoing opportunities for learning and professional development
  • Tools and workplace flexibility to support meaningful impact
  • Leadership development through insights, coaching, and confidence building
  • A diverse and inclusive workplace culture
  • Collaboration with global EY teams on engaging projects
  • Access to learning, skills, and insights across EY’s global delivery network

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