Climate Risk Analyst | Catastrophe Modelling

AXA UK; Greater London; Hybrid; GBP 70,000 - 120,000; Full time

Benefits offered by this job

Flexible working arrangements

Hybrid work model

Professional development

Job summary

AXA UK is seeking a Climate Chance Analyst to advance atmospheric perils modelling and climate risk assessment, translating scientific findings into practical insurance solutions.

You will lead small research projects, develop risk assessment techniques, and collaborate with internal teams and external partners to validate catastrophe models.

The role requires a PhD in a scientific field, strong Python/R skills, and the ability to communicate complex results to senior leadership.

Qualifications

• PhD in a scientific discipline required.
• Strong programming and data analysis skills in Python or R.
• Extensive experience in catastrophe risk modelling and model validation.

Responsibilities

• Support analytical reviews and validation of catastrophe models focusing on atmospheric perils and climate change impacts.
• Develop and refine risk assessment techniques for catastrophe risk quantification.
• Translate external scientific research into actionable insurance practices and risk management strategies.
• Conduct independent scientific research aligned with AXA UK’s business interests and risk profile.
• Manage small research projects from initiation to completion with internal teams and external partners.

Skills

Python programming

R programming

Data analysis

Scientific communication

Project management

Stakeholder collaboration

Risk modelling

Model validation

Education

PhD in a scientific discipline

Tools

Python

R

Job description

AXA UK is seeking a Climate Chance Analyst to advance atmospheric perils modelling and climate risk assessment, translating scientific findings into practical insurance solutions.

You will lead small research projects, develop risk assessment techniques, and collaborate with internal teams and external partners to validate catastrophe models.

The role requires a PhD in a scientific field, strong Python/R skills, and the ability to communicate complex results to senior leadership.