Data Scientist

Arbol is a global climate risk coverage platform and FinTech company offering full-service solutions for any business looking to analyze and mitigate exposure to climate risk. Arbol’s products offer parametric coverage which pays out based on objective data triggers rather than subjective assessment of loss. Arbol’s key differentiator versus traditional InsurTech or climate analytics platforms is the complete ecosystem it has built to address climate risk. This ecosystem includes a massive climate data infrastructure, scalable product development, automated, instant pricing using an artificial intelligence underwriter, blockchain-powered operational efficiencies, and non-traditional risk capacity bringing capital from non-insurance sources. By combining all these factors, Arbol brings scale, transparency, and efficiency to parametric coverage.In this role, you will research, develop, and apply machine learning tools to model and price climate and weather risk. You will work with diverse weather and geospatial datasets covering a suite of phenomena, from traditional weather-station readings of temperature and precipitation, to radar measurements of hail stone sizes, to satellite indices of vegetation content. You will learn how to use our existing catalog of pricing and modeling tools, engage in their improvement and maintenance, and develop new methodologies. We are open to a range of experience levels for this position.About the TeamThe analytics team is responsible for making sense of the terabytes of data Arbol has at its disposal. It forms the connective tissue between more client-facing teams, such as sales, and back-end roles like data engineering. You’ll be joining a small team of data scientists and researchers and will have a unique opportunity to impact many levels of the firm. This is an ideal position for someone interested in building machine learning systems while taking a deep dive into the insurance industry.\nWhat You'll Be DoingCollaborate wi