Climate Scientist

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

Job summary

A leading recruitment platform in London seeks a Scientist specialized in Loss Modelling to develop models quantifying climate-related risks. The ideal candidate has robust programming skills in Python or R and experience in catastrophe modelling. This hybrid role offers a dynamic environment focused on innovative R&D.

Qualifications

• Experience in building and calibrating loss models across multiple perils.
• Strong programming skills in Python, R, or similar.
• Knowledge of machine learning applications in climate risk.

Responsibilities

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

Skills

Building and calibrating statistical/mathematical loss models

Proficiency with geospatial data

Programming skills in Python or R

Excellent communication skills

Experience in catastrophe modelling

Applied statistical skills

Knowledge of 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

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 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).

If this role looks of interest, please apply below.

Please note - this role does not offer sponsorship.