Senior Climate Risk Analyst with geospatial experience Vila Real

Senior Climate Risk Analyst with geospatial experience
Vila Real
Vila Real, Vila Real District, Portugal

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 Saa
S platform, Location Risk Intelligence, we deliver an advanced geospatial solution that empowers clients with
- 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, net
  CDF, shapefiles)
• Knowledge of climate risk concepts, physical hazard datasets, and vulnerability assessment techniques
• Solid understanding of supply chain modelling desirable
• Strong
  - solving skills and ability to work in interdisciplinary teams
• Strong communication skills, clear documentation habits, and readiness to collaborate remotely with multidisciplinary teams

Responsibilities:

• Develop analytical frameworks for climate risk assessments
• Benchmark physical risk exposure of assets and locations using internal datasets,
  - 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