About this role
Analytics & Modeling Analyst, Coastal Flood
London, United Kingdom
Moody's is transforming how the world sees risk. We unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We strive to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. We decode risk to unlock opportunity, helping clients navigate uncertainty with clarity, speed, and confidence.
If you are excited about this opportunity but do not meet every single requirement, please apply. You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.
Skills and Competencies
- Experience working with high-performance clusters in a UNIX or Linux environment
- Experience with either numerical models (such as AGCMs, OGCMs, CGCMs, regional models or mesoscale models), handling large data sets, or statistical modelling
- Strong programming ability in scientific and analytical programming languages (e.g. Python, R, Fortran)
- Strong analytical skills and ability to effectively communicate insights to internal and external stakeholders
- Familiarity and interest in state-of-the-art ML methods would be highly advantageous
- Previous experience in catastrophe modeling, or specific expertise in modelling natural hazards is valued but not necessary
- Experience in using GitHub or similar code management software is advantageous
- Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use
Education
- PhD in a field related to storm-surge or other aspects of coastal ocean modelling. Strong candidates with a relevant MSc and appropriate research or work experience would also be considered
Responsibilities
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We're looking for a candidate with a background in coastal dynamics, oceanography, or coastal engineering and a desire to use that expertise in quantifying the risks that coastal flooding drives.
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Building and developing storm surge, wave and coastal defence model components
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Calibration and validation of model results (both hazard and loss) through comparison to observed data and benchmarks
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Advancement of our models through research and implementation of novel scientific techniques
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Communicating research to clients and other stakeholders
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About the Team
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Moody's 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 a multidisciplinary team of scientists and engineers, building mathematical models that predict damage caused by tropical storms, extra-tropical storms, thunderstorms, coastal floods, freshwater floods and tsunamis. We use a combination of observed data, reanalysis data, numerical, statistical and engineering models and data assimilation. We are the pioneers in the development and application of complex statistical and numerical modelling methods for the quantification of natural hazard risk, and our risk models are the most detailed and comprehensive models of natural catastrophes produced anywhere in the world. There is a strong focus on collaboration and innovation within the team with regular meetings to share methodologies and research.
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Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
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Employment is contingent upon compliance with policy requirements.
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