Cyclone Hazard Modeler

Model Development/Modeling London, United Kingdom

Overview

We are one of the most exciting companies you’ve probably ‘never’ heard of, unless you’re one of our hundreds of clients in the (re)insurance, banking or hedge fund sector. We lead an industry we helped pioneer and ultimately our work makes a true impact on the world at large. How we understand and manage risk affects everybody and our passion is nothing less than creating a more resilient world through a better understanding of catastrophic events.

Risk Management Solutions (RMS) is the world's leading provider of mathematical models and information related to the financial impact of natural catastrophes. Our Model Development department has over fifty Ph.D. scientists and engineers based in London, building mathematical models that predict the distributions of possible damage due to the effects of tropical storms, extra-tropical storms, thunderstorms, storm-surges, and freshwater floods. To that effect, we use observational and reanalysis data, as well as numerical, statistical, data science, and engineering models.

We are the pioneers in the development and application of cutting-edge, combined statistical and numerical modelling methods for the quantification of natural hazard risk, and our models are the most detailed and comprehensive models of natural catastrophes produced anywhere in the world.

RMS has 1,200 employees in 11 countries, including offices in Newark (CA-USA), Noida (India), London (UK), Hoboken (NJ-USA), and Zurich (Switzerland).

Objective of the Role

This role involves researching the hazard of tropical storms and developing statistical and mathematical models which quantify the risk they pose to society. It presents a unique opportunity to work in a multidisciplinary team of catastrophe modelers including statisticians, mathematicians, physical scientists and engineers, to build models which are critical to our Re/Insurance clients and essential to the other markets which RMS serve.

Key Responsibilities:

The successful candidate will perform research and development work in tropical cyclones and their extreme behavior, with the overarching goal to quantify their loss potential. S/he will work closely with hazard, vulnerability, exposure, and financial modelers to ensure the accuracy, efficiency and appropriateness of the final modelling product.

Essential Requirements:

The ideal candidate’s qualities, skills and attributes follow:

  • PhD in a relevant subject (e.g. Atmospheric Science, Statistics, Climate Science, Applied Mathematics, or closely related areas).
  • Strong mathematical foundation with a focus in statistics, probability, and computational science.
  • Demonstrated success in developing sophisticated mathematical models in Academic or Industrial environments.
  • Experience with climate analyses & data, and an understanding of tropical storms processes.
  • Experience working with large and complex datasets.
  • Strong ability in modelling languages and modern systems of scientific repeatability and engineering scalability.
  • Experience with high-performance clusters and strong user skill in a Linux/Unix environment.
  • Ability to communicate analysis results and insights effectively both internally and with external business partners.

Advantageous:

  • Demonstrated success to manage priorities and deadlines and to work independently in a highly dynamic and diverse environment with multiple concurrent goals and with a diverse team of scientists and engineers.
  • Excellent time management and planning skills with a commitment to delivery.
  • Driven and committed, demonstrating initiative and self-motivation.
  • Critical thinking and problem-solving skills.
  • Attention to detail and intense curiosity.
  • Familiarity and interest in the re/insurance business domain.
  • Familiarity and interest in state-of-the-art modelling methods including AI and ML.
  • Willingness to pursue continued education in support of the role and team goals.

Salary range: £46,852 - £63,388 per year
Opening date: 06/12/2019
Closing date: 05/01/2020

Please provide your CV highlighting your salient education and experience, and a Cover Letter demonstrating how these meet the requirements of the position.

To All Recruitment Agencies: RMS does not accept unsolicited agency resumes and will not be responsible for the payment of placement fees related to unsolicited resumes submitted to open positions, job aliases, or to our employees.