Zurich, Zurich, CH

Senior Nat Cat Specialist (Hybrid / m/f/x/d / 80% - 100%)

Are you looking for a unique opportunity to bring our catastrophe model development to the next level? Do you want to be at the intersection of science and its business application in re/insurance? 


About the Role


In this role you will work closely with peers in our global Cat Perils team as well as with the teams who apply the models for making the right business decisions. 


Key responsibilities: 


  • Contribute to Cat Perils global agenda with a business impact attitude, delivering tangible outcomes with a sense of urgency
  • Build, maintain, and communicate the next generation of Nat Cat models globally and for Europe, Middle East and Africa (EMEA) in particular, with a focus on flood and, other weather perils
  • Contribute to and lead cross regional team projects
  • Establish yourself as a point of contact for Nat Cat related questions, with senior expertise in flood and other weather perils.


About the Team


We are looking for a new team member to join the Cat Perils EMEA & Methods team, part of Swiss Re's global in-house natural catastrophe modelling unit. We create value for Swiss Re by driving confident Nat Cat decisions.
With our proprietary modelling technology for natural catastrophe perils, we bring latest science to underwriting decision-making, working closely with peers in re/insurance underwriting and further support our business in all matters related to natural catastrophe risk.


About You


With you, we win a colleague with excellent social competences who contribute actively to our team spirit.


Technical skills and education:


  • M.Sc. or Ph.D. degree in quantitative natural sciences, engineering or equivalent
  • 5+ years of industry or post PhD academic experience in natural catastrophe modelling (probabilistic models, flood), preferably in a re/insurance context; underwriting experience is a plus
  • In-depth knowledge of climate-change-related topics and extreme weather events in particular
  • Professional network within the academic and/or industry natural catastrophe modelling community. OASIS experience is a plus
  • Strong analytical and programming skills (e.g., Python, Matlab, git), record in successfully developing data analysis applications; experience with statistics and machine learning is a plus
  • Strong project management, communication, and presentation skills
  • Excellent written and verbal English, additional languages are a plus


Personal skills and interests:


  • High degree of own initiative and interest for interdisciplinary work
  • You approach problems with curiosity and flexibility, are a fast learner and eager to take responsibility.
  • Ability to build trust with peers in business teams by providing relevant and deep insights
  • Pragmatic to balance technical excellence with business needs
  • Ready to own and curious in how our insights impact UW decisions
  • Agile in response to stakeholders' needs focusing on where it matters most


We are looking forward to your application!


About Swiss Re


Swiss Re is one of the world’s leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 14,000 employees across the world.

Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking. We embrace a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics. In our inclusive and flexible environment everyone can bring their authentic selves to work and their passion for sustainability.



Reference Code: 128403 



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