Senior Research Analyst – Natural Catastrophe

Overview

In this role you lead validation of catastrophe models and drive innovative research to improve how catastrophe risk is understood and managed. You collaborate across underwriting, risk, modelling, and external forums to share insights and shape risk governance. You will develop and communicate findings that influence model adjustments, climate risk understanding, and non-modelled perils. This position offers breadth across teams and opportunities to influence Lloyd’s syndicate practices while showcasing technical leadership.

Pay / Benefits

• hybrid working
• 3 days in the office
• collaborative culture
• opportunity to influence risk strategies
• global exposure to Lloyd’s network
• professional development opportunities

Responsibilities

• Lead projects to validate catastrophe models, designing testing plans, performing scientific analyses, and delivering regulatory documentation and stakeholder communications
• Assist in developing MS Amlin’s View of Risk and implement model adjustments when required
• Undertake innovative research on catastrophe risk, including climate change and non-modelled perils
• Produce catastrophe risk governance documentation and research briefings
• Provide catastrophe risk expertise to internal stakeholders (underwriters, exposure management, catastrophe modellers)
• Represent MS Amlin at external events and committees (conferences, Lighthill Risk Network)
• Stay abreast of industry trends in natural hazards research
• Contribute to event response efforts with real-time insights, loss assessments, and cross-team coordination
• Operate in alignment with Business Ethics and regulatory requirements
• Share scientific knowledge across the team and wider business
• Act as an ambassador to raise MS Amlin’s profile in the market

Key requirements

• PhD or equivalent in a field relevant to natural catastrophe risk (preference for meteorology, atmospheric science, hydrology/flood risk, or wildfire risk)
• Strong analytical and quantitative skills with experience handling large data sets
• Programming experience (Python)
• Spatial visualization experience (QGIS)
• Proficiency in communicating complex scientific ideas to non-technical audiences
• Strong critical thinking and decision-making abilities
• Project management and deadline-driven mindset
• Experience with catastrophe model validation (e.g., Moody’s RMS) is advantageous
• Track record in developing natural hazard models in insurance or academia; strong statistical background advantageous

• Collaborative mindset
• Clear written and oral communication
• Critical thinking
• Python programming
• QGIS spatial visualization
• Large data analysis

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