Senior Climate Risk Analyst with geospatial experience
Location: Remote from Spain (Spanish employment contract)
We are looking for a passionate Risk Analyst to help our product and modelling teams develop asset level and exposure data assets, as well as improve name matching abilities.
Project Overview:
Our modular climate risk offering is built to meet the complex needs of insurers, banks, corporates, and real estate investors. Through the SaaS platform, Location Risk Intelligence, we deliver an advanced geospatial solution that empowers clients with location-specific climate risk data worldwide, enabling them to make informed decisions on climate risk reporting, underwriting, and investments.
Requirements:
* Strong background in quantitative analytics, climate risk assessment, or applied economics
* Demonstrated experience in risk modelling, or economic assessments
* Proficiency in programming languages such as Python, R, or MATLAB for scientific and geospatial data analysis
* Experience with geospatial data handling (e.G., GIS tools, netCDF, shapefiles)
* Knowledge of climate risk concepts, physical hazard datasets, and vulnerability assessment techniques
* Solid understanding of supply chain modelling desirable
* Strong problem-solving skills and ability to work in interdisciplinary teams
* Strong communication skills, clear documentation habits, and readiness to collaborate remotely with multidisciplinary teams
* At least B2 level of English.
Responsibilities:
* Develop analytical frameworks for climate risk assessments
* Benchmark physical risk exposure of assets and locations using internal datasets, third-party data, and industry standards
* Design and document analytics workflows, ensuring reproducibility and transparency
* Collaborate with data scientists, software developers, and climate experts to ensure model robustness and scalability
* Integration of new scientific research and climate change scenarios to enhance climate risk assessments
* Document modelling methodologies, assumptions, and validation processes
* Present model results and risk assessments to internal stakeholders