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Data scientist

Harnham Search & Selection
Data scientist
Posted: 28 August
Offer description

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 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.

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