Climate Change Modeler

Risk Management Solutions (RMS)
London, United Kingdom
Position Type: 
Organization Type: 
Private Sector
Experience Level: 
Not Specified
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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.

We use a combination of observations, reanalysis data, numerical, statistical and engineering models. We are the pioneers in the development and application of 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.

Our clients include several hundred insurance and reinsurance companies as well as brokers, banks, asset managers, hedge funds, regional and local governments, and multilateral agencies.

Objective of the Role

RMS are currently recruiting for a position related to the modelling of risk due to Climate Change and Variability.

The modelling work carried out by the team encompasses all steps from climate science R&D, mathematical modelling and data science, to the quantification of impacts for portfolios of subjects of climate risk. The model development department has an engaged working environment with a clear and motivated scientific and technological culture.

Key Responsibilities & Deliverables:

The successful candidate will develop methodologies and integrate understandings into RMS’ climate risk models pertaining to climate change and variability. S/he will work closely with other hazard, vulnerability, exposure, and financial modelers to ensure the accuracy, efficiency and appropriateness of the final modelling products. S/he will work within a team dedicated to development of modelling products related to climate change and variability.

Essential Requirements:

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

  • PhD in a relevant subject (e.g. Climate Science, Atmospheric Science, Hydrology, Water Resources, Geophysics or closely related areas).
  • Research experience with, and solid understanding of climate processes and their variability including Climate Change.
  • Strong mathematical foundation with focus on physics-based and numerical modelling of natural systems
  • Demonstrated ability 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.
  • Experience working with large and complex datasets.
  • Strong ability in modelling languages (e.g. R, Python), and modern systems of scientific repeatability and engineering scalability (e.g. GitHub).
  • Strong user skill in a Linux/Unix environment.
  • Ability to communicate effectively insights and analyses.


  • Relevant experience within a re/insurance company and/or model vendor.
  • Peer-reviewed scientific publications in areas related to risk and/or climate change.
  • Experience communicating complex scientific and risk modelling concepts to external stakeholders (in a commercial setting).
  • Familiarity with tropical cyclone catastrophe risk modelling.
  • Strong foundation in probability and statistics.
  • Postdoctoral research experience.

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

About RMS

There’s a 1% chance an earthquake will cause $50 billion of insured loss within the next 12 months and a 5% chance that a hurricane will cause $60 billion of insured losses next year. At RMS, we turn risks into real numbers. How? By building simulation models that allow insurers and investors to understand and manage their global risks--from hurricanes, quakes, and wildfires, to cyberattacks, terror attacks, and pandemics. Why? We want to build a more resilient world, and we’re on a mission to help make every risk known.

Insurers, reinsurers, investors, financial institutions, governments, and NGOs trust RMS solutions to better understand and manage catastrophe risks. RMS was founded in 1989 by Stanford scientists who created our first model for California Earthquake. Today, RMS has some 1,300 employees across 13 offices in the US, London, Bermuda, Zurich, India, China, Japan, Singapore, and Australia, and over 1,000 products and models now covering six continents.

RMS helped pioneer the natural catastrophe model market we now lead – and we continue to innovate. In May 2019, we announced RMS Risk Intelligence™ (RI), an open-standard platform for strategic risk management. Through this purpose-built platform, clients can tap into RMS HD models, rich data layers, intuitive applications and APIs that simply integrate into existing enterprise systems to support business decisions across underwriting, risk selection, mitigation, and portfolio management.

How we understand and manage risk affects everyone and our passion is nothing less than creating a more resilient world through a better understanding of catastrophic events. Join our team of leading scientists, developers, industry experts, and world-class professionals. Together, RMSers make a difference on a truly global scale.

Visit to learn more and follow us on LinkedIn and Twitter

RMS is proud to be an equal opportunity workplace. We are committed to equal employment opportunity without regard to race, color, creed, gender, religion, marital status, registered domestic partner status, age, national origin or ancestry, physical or mental disability, genetic characteristics, sexual orientation, or any other classification protected by applicable local, state, or federal law.

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.

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