Modeling Lead

About the role

This is a remote position based in the US with occasional travel.

What You’ll Do

• Actuarial Modeling & Execution
• Build, enhance, and maintain actuarial models for pricing, reserving, projections, and financial analytics.
• Translate modeling standards and approaches set by the Head of Modeling into robust, production-ready implementations.
• Implement, test, and maintain actuarial assumptions, experience studies, and stress/scenario analyses.
• Support recurring and ad-hoc model runs across development, validation, and production environments.
• Refactor and optimize models for performance, transparency, and scalability.

Enterprise Data Model & Modern Data Pipeline Support

• Help design and maintain the enterprise actuarial and finance data model, ensuring consistency across pricing, valuation, financial reporting, and analytics.
• Partner with Data Engineering and Technology teams to support end-to-end data pipelines (ingestion → transformation → storage → consumption) that make actuarial outputs reliable and reusable.
• Support data validation, reconciliation, and controls between source data, model inputs/outputs, and downstream reporting.
• Contribute to a modern data lake / lakehouse approach where appropriate, and support use cases across platforms such as Snowflake and open table formats.

Modeling Infrastructure, Controls & Governance

• Contribute to shared modeling frameworks, libraries, and reusable components.
• Support model versioning, documentation, testing, and change management processes.
• Aid in internal model reviews, validation efforts, audit requests, and regulatory support.
• Identify model and data risks, limitations, and dependencies, and communicate them clearly.

AI-Enabled Modeling & Platform Evolution

• Partner with the Head of Modeling to apply AI and automation to improve speed and quality of model development and enhancement.
• Use AI-enabled tooling to support activities such as development acceleration, test generation, documentation drafting, model/result validation workflows, and scenario exploration—while keeping human actuarial judgment in control.
• Evaluate new approaches pragmatically, prioritizing auditability, reproducibility, and measurable impact.

Cross-Functional Partnership

• Work closely with Finance, Product, Data, Technology, and Operations teams to ensure actuarial models and data outputs are actionable and consumable.
• Translate actuarial and financial results into clear insights for non-actuarial stakeholders.
• Support strategic initiatives including new product development, reinsurance analysis, and platform evolution.