Interested in exploring the world of Catastrophe Modelling? Curious about working in a dynamic and enriching environment of a multinational company? We are offering a unique opportunity to leverage your skills in a highly specialized and diverse global team.
Zurich’s Group Accumulation Management function delivers thought leadership and actionable insights to the business regarding natural and man-made catastrophes. Using both internal and externally sourced Cat Modeling capabilities, we assess accumulation risk globally. Our comprehensive approach to accumulation risk is an essential component of Zurich’s Risk Management and Underwriting function that supports the optimization of our portfolios, delivers sustainable and profitable growth and is striving to understand current and emerging risks including cyber, casualty cat and climate change. The Cat Research & Development team plays a key role on our transformation journey embracing science and technology.
We are looking for an enthusiastic intern with a deep knowledge of at least one natural catastrophe field and/or who has a strong background in statistics, risk assessment, computer science and/or machine learning. The optimal candidate is eager to extend his/her work to different cat topics and is keen to make a positive impact on the overall business.
What you will do
1. Support natural and man-made catastrophe risk related research and development projects for the Group Accumulation Management function and translate the research insights into positive impacts for the business.
2. Adapt existing models to reflect risk changes and climate change scenarios, and leverage model insights to generate business opportunities.
3. Leverage data analytics, artificial intelligence and machine learning techniques to enhance the Zurich View of risk, data quality assessment and/or augmentation and to transfer insights to non-modelled regions, etc.
What you bring
4. Completed Bachelor’s degree level qualification in a quantitative field (e.g. Engineering, Mathematics, Physics, Geography)
5. Quantitative background and strong analytical skills
6. Working experience in programming a high-level language like R or Python
7. An active enrolment at University is required