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Senior Catastrophe Research Analyst

Job in London, Greater London, W1B, England, UK
Listing for: American International Group (AIG)
Full Time position
Listed on 2026-10-30
Job specializations:
  • Research/Development
    Data Scientist
Job Description & How to Apply Below
Senior Catastrophe Research Analyst Join us as a Senior Catastrophe Research Analyst to take your career to the next level with a global market leader.

Make your mark in Cat ModellingAIG’s model validation and research group consists of team members in the US & London, and an outsourced team in Bengaluru, India. The role will involve collaboration with this team, and with multiple external vendors (Moody’s, Verisk, Kat Risk), as well internal teams building bespoke tools. The job holder will lead the review of and take ownership of specific peril region models as directed by the Head of Catastrophe Research & Validation.

How you will create an impact

This role will be part of AIG’s Catastrophe Research & Validation Team. You will support the development of AIG’s internal view of risk for Natural Catastrophe, Terrorism, and other First Party Perils. Working with the Head of Catastrophe Research & Validation and other Cat Modelling Leaders, the job holder will support the implementation of industry leading analytics, research practices, and model development across the organisation.

Some of the key responsibilities include:

Lead innovative research on catastrophe risk, with a focus on peril regions most material to AIGSupport the development standardised best practices and view of risk strategy

Support end to end catastrophe model evaluation across the company:

Implementing AIG’s View of Risk Validating new and existing vendor models

Proposing adjustments to vendor out of the box views

Implementing model change and upgrades

Support AIG’s assessment of climate change and impacts to climate related perils worldwide

Support climate change engagement with internal and external stakeholders

Work with Enterprise Risk Management partners to ensure views of risk are clearly documented and communicated in line with AIG’s model risk management policies

Support short and medium term efforts to transform internal catastrophe modelling process

Closely collaborate with functions such as Risk Engineering, Actuarial, Underwriting, and ERM to share insights and best practices across the organisation

Partner with the Data Office on strategic data initiatives, including supporting vendor/data provider capability assessments and contract reviews.

What you'll need to succeed

PhD or Master’s degree in Climate Science, Natural Hazards, Applied Statistics, or a related subject3+ years of experience in catastrophe research or model development, experience using RMS is preferred

Excellent understanding of the science of catastrophe modelling, and hands on experience writing model reviews and validationA knowledge of catastrophe models including their strengths and weaknesses, and demonstrated expertise in the science of one or more peril regions

An understanding of climate change and its impact on insurance, and an interest in developing analytics and thought leadership in this areaA keen interest in the impact of modelling, on Underwriting decision making

An ability to communicate technical concepts in a non-technical manner

Excellent communication, presentation, and interpersonal skills

Strong programming skills including R, Python, and SQL#LI-AIGAt AIG, we value in-person collaboration as a vital part of our culture, which is why we ask our team members to be primarily in the office. This approach helps us work together effectively and create a supportive, connected environment for our team and clients alike.

Enjoy benefits that take care of what matters

At AIG, our people are our greatest asset. We know how important it is to protect and invest in what’s most important to you. That is why we created our Total Rewards Program, a comprehensive benefits package that extends beyond time spent at work to offer benefits focused on…
Position Requirements
10+ Years work experience
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