Catastrophe Modeling Lead — Global Risk & Validation

Aig Inc; Boston (MA); On-site; USD 120,000 - 145,000; Full time

Benefits offered by this job

Competitive benefits

Total Rewards Program

In-office culture

Job summary

AIG’s Catastrophe Research & Validation Team is seeking a Catastrophe Research Manager to lead model validation and research across perils and regions. You will manage analysts across locations and collaborate with external vendors to enhance AIG’s view of risk.

You will support climate risk initiatives, interact with senior management, regulators, and risk functions to translate complex catastrophe science into actionable insights and robust risk assessments.

Qualifications

• 6+ years of catastrophe research or model development experience; RMS preferred.
• PhD or Master’s in Climate Science, Natural Hazards, Applied Statistics, or related field.
• Experience at an underwriting company or broker is a bonus.
• Strong understanding of catastrophe modelling and ability to present to stakeholders.

Responsibilities

• Lead Model Validation & Research for specific perils and regions, mentoring a team in Bengaluru.
• Collaborate with Cat Modelling Leadership to evaluate models and standardise best practices.
• Support end-to-end catastrophe model evaluation and implement risk views.
• Develop relationships with reinsurers and model vendors to benchmark risk views.
• Contribute to climate change analyses and regulatory engagements.
• Coordinate with Risk Management, ERM, and Data Office to share insights.

Skills

R

Python

SQL

Leadership

Communication

Education

PhD or MSc in climate science

Tools

RMS knowledge

Job description

AIG’s Catastrophe Research & Validation Team is seeking a Catastrophe Research Manager to lead model validation and research across perils and regions. You will manage analysts across locations and collaborate with external vendors to enhance AIG’s view of risk.

You will support climate risk initiatives, interact with senior management, regulators, and risk functions to translate complex catastrophe science into actionable insights and robust risk assessments.