Climate Scientist

ZipRecruiter; City Of London; Hybrid; GBP 68,000 - 80,000; Full time

Job summary

A leading global climate risk consultancy is seeking a Scientist specializing in Loss Modelling in London. This hybrid role involves developing models to assess climate-related physical risks, focusing on natural catastrophes. The ideal candidate will have expertise in statistics, geospatial data, and programming. Strong communication skills are essential as you'll share insights with stakeholders. This position does not offer sponsorship.

Qualifications

• Experience building and calibrating statistical/mathematical loss models.
• Proficiency with climate and Earth observation geospatial data.
• Strong programming skills in Python, R, or similar.

Responsibilities

• Develop loss models to quantify climate-related risks.
• Calibrate and validate models using data sources.
• Document methodologies and communicate insights.

Skills

Statistical/mathematical model building

Geospatial data proficiency

Programming in Python or R

Excellent communication skills

Self-starter in R&D

Catastrophe modelling experience

Bayesian statistics

Machine learning applications

Familiarity with cloud platforms

Job description

Overview

Scientist – Loss Modelling (Physical Risk from Weather and Climate)

London – Hybrid

Up to £80,000

About the Role

Our client is building global-scale models to assess the physical risks of climate change and is looking for a Scientist with expertise in applied statistics and physical loss modelling.

This role is ideal for someone experienced in natural catastrophe modelling and confident working with large geospatial and financial loss datasets.

You’ll contribute to the development, calibration, and validation of loss models that project climate-related physical impacts such as floods, subsidence, storms, droughts, and wildfires — helping clients assess and manage climate risks effectively.

Key Responsibilities

• Develop loss models to quantify climate-related risks, with a focus on estimating asset vulnerabilities.


• Calibrate and validate models using a wide range of qualitative and quantitative data sources.


• Contribute to building a robust and adaptable loss modelling framework.


• Document methodologies and communicate scientific insights to stakeholders, clients, and at industry events and conferences.

What We’re Looking For

• Experience building and calibrating statistical/mathematical loss models, ideally across multiple perils.


• Proficiency with geospatial data (climate and Earth observation) and economic damage datasets.


• Strong programming skills in Python, R, or a similar programming language.


• Excellent communication skills, able to explain complex concepts to non-technical audiences.


• A self-starter who thrives in a fast-paced R&D environment.


• Experience in catastrophe modelling, especially around exposure and vulnerability.


• Applied statistical skills such as Bayesian statistics, uncertainty quantification, or Extreme Value Theory.


• Knowledge of machine learning applications in climate risk.


• Familiarity with cloud platforms (e.g., AWS, Google Cloud).

Please note - this role does not offer sponsorship.