A world of opportunities

Type of employment

Select how often (in days) to receive an alert:

(Senior) Nat Cat Specialist - Atmospheric Perils (severe convective storm) (80-100%)

• Are you looking for a unique opportunity at the intersection of science, engineering, and business? Do you want to be part of our effort to bring natural catastrophe modeling to the next level? Do you want to help us increase our confidence in natural catastrophe risk assessment and decision making? Then, this role may be for you
• As a member of the Cat Perils team, you will join our efforts to develop innovative models used for quantifying the physical and economic impacts of natural catastrophes. In your role as a Natural Catastrophe (Nat Cat) Specialist with expertise in Atmospheric Perils, you will:
• Build, develop, and improve models for assessment of risk associated with natural catastrophes, primarily severe convective storms, but also tropical cyclones, windstorms, and/or wildfires
• Apply the latest scientific methods, concepts, and technologies in novel and innovative ways in a fast-paced business environment
• Acquire and analyze data to quantify the impacts of natural catastrophes on buildings, facilities, and infrastructure in different regions of the world
• Establish yourself as an expert on natural catastrophe risk and modeling within Swiss Re, and effectively communicate these risk views internally and externally
• This position can be filled at Assistant Vice President (AVP) or Vice President (VP) level. Salary and corporate band will be commensurate with candidate experience

The catastrophe perils (Cat Perils) department is responsible for development and advancement of Swiss Re’s global Nat Cat risk assessment framework, models, and tools. The team consists of approximately 50 dedicated scientists and engineers in multi-faceted technical fields. We develop proprietary Nat Cat models and risk views, informed by the latest science and engineering as well as our unique underwriting experience and expertise, to grow Swiss Re's edge in Nat Cat re/insurance. We create value for Swiss Re by driving confident Nat Cat decisions, in close collaboration with peers in underwriting and other functions

Requirements

• M.Sc. or Ph.D. degree in
• meteorology; applied physics; atmospheric, climate, or other natural sciences; or a related technical field
• Industry or academic experience in atmospheric/climate/natural catastrophe modeling. Modeling experience in a re/insurance context is a plus
• Strong analytical and programming skills (e.g., ), and experience using statistical tools and methods to solve applied problems
• Minimum 5 years of experience with natural catastrophe modeling in re/insurance, or a closely related sector
• Demonstrated leadership and/or project management ability in a relevant professional setting

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. We cover both Property & Casualty and Life & Health. 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., , If you are an experienced professional returning to the workforce after a career break, we encourage you to apply for open positions that match your skills and experience