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.
About the Role
In this role, you will research, develop, and implement AI and automation tools for complex insurance operations. You will work with disparate unstructured data sources using the latest LLM, vision, and agentic models to solve a variety of classification and decision-making tasks. This will require exciting technical insights coupled with business understanding gained through interaction with other teams.
We are looking for someone with a quantitative background and an interest in applying that skillset toward business-driven research problems at the intersection of AI and insurance.
About the Team
The quant 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, engineers and meteorologists 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.
