Roland Schöbi is driven by the goal to estimate and quantify risks and uncertainties when information is scarce, incomplete, or simply missing. He works at Zurich Insurance in the catastrophe R&D team looking at new ways of using machine learning techniques in the field of catastrophe modelling besides being responsible for Zurich’s View of Risk. Together with his colleagues, he translates the latest scientific findings on natural and manmade perils into tangible risk insights. Previously, Roland worked on his Ph.D. degree at ETH Zurich on uncertainty quantification techniques in the context of imprecise probabilities, which included various applications from engineering to physics and economics.