Climate X

tech startup

ScienceTeamInternship

London, England, United Kingdom FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Entry candidates.

The Brief

“Science Team Internship at Climate X. Skills: hazard and loss modelling, validation, data workflows, geospatial analysis, applied modelling. contributing to our hazard and loss modelling, validation, and data workflows. prototyping computer vision and machine learning techniques to characterise buildings at a global scale”

Industry & Context.

tech startup
Problems you'll solve

problem solving in a product driven environment balancing real world constraints

What They're Looking For.

Must Have

graduate students or recent postgrads, in a quantitative field such as climate science, meteorology, geography, physics, engineering, maths, statistics, computer science, or related, Comfortable working with data, writing code (typically Python)

Nice to Have

Familiarity with ML/statistical modelling workflows, Experience working with large datasets or cloud tooling

What You'll Do.

contributing to our hazard and loss modelling

prototyping computer vision and machine learning techniques to characterise buildings at a global scale

exploring the potential impacts of large-scale climate scenarios and developing approaches to quantify them

modelling water scarcity under current and future climate conditions to support investment and infrastructure decision-making

How You'll Work.

Team & Collaboration

work alongside scientists and engineers

Communication Scope

able to communicate findings clearly

Full Job Description

About Climate X Climate X is a leading tech startup that quantifies present and future financial risk from climate and hazards. We build scientific models and software that help organisations understand exposure, assess risk, and make better decisions under climate uncertainty. Firms (e. g. banks, insurance companies, and real estate investors) use Climate X models to turn future climate hazards into decision-ready risk and loss outputs at both asset and portfolio level. Banks quantify exposure and potential losses for risk management, stress testing, and disclosure workflows. Estate firms use generate asset- and portfolio-level reporting aligned to frameworks like TCFD, SFDR, EU Taxonomy, GRESB, and CRREM, and compare climate risk across portfolios/regions. The opportunity We are looking for Science Interns to join our team this summer. You will work alongside scientists and engineers on real products and research, contributing to our hazard and loss modelling, validation, and data workflows. You will gain first hand experience of problem solving in a product driven environment balancing real world constraints. What you will do We are looking for interns who would be interested in working on projects around the following themes: • Asset AI characterisation — prototyping computer vision and machine learning techniques to characterise buildings at a global scale. • Climate Tipping Points — exploring the potential impacts of large-scale climate scenarios and developing approaches to quantify them. • Climate & Water Risk — modelling water scarcity under current and future climate conditions to support investment and infrastructure decision-making. What we are looking for Currently graduate students or recent postgrads, in a quantitative field such as climate science, meteorology, geography, physics, engineering, maths, statistics, computer science, or related Comfortable working with data and writing code (typically Python) Experience with geospatial tools (GeoPandas,

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