Analytics and Modeling Intern - Coastal Flood

PassFort; Greater London; On-site; GBP 18,000 - 28,000; Full time

Job summary

Moody's Analytics invites applications for the Analytics and Modeling Intern - Coastal Flood in London. You will support the development and evaluation of machine learning and surrogate models to improve coastal flood risk modelling, working with Python and C++ on HPC clusters.

Explore Graph Neural Operators to reduce computation while preserving accuracy in coastal dynamics. We seek a Master’s or PhD student in Coastal Ocean Modelling or ML, able to start a 4‑month internship in March 2027.

Qualifications

• Experience working with HPC clusters in a Linux environment and using Git for version control.
• Strong programming skills in Python and C++ for scientific and analytical tasks.
• Experience with numerical models for ocean or wave modelling, or statistical modelling approaches.
• Experience handling and analysing large datasets.
• Familiarity with modern ML methods such as Graph Neural Networks (GNNs) and Fourier Neural Operators (FNOs).
• Familiarity with model performance evaluation and model inter-comparison methods.
• Strong analytical skills with ability to interpret results and communicate insights effectively.
• Proficiency in AI concepts and hands-on use of AI tools to streamline workflows and solve business challenges; awareness of AI risk management.

Responsibilities

• Support the development and evaluation of ML and surrogate models to improve coastal flood risk modelling.
• Characterize coastal flooding dynamics to identify key predictors and processes.
• Enhance existing ML models for coastal risk.
• Explore ML methods (e.g., mSWE-GNN) to improve variability and extreme dynamics.
• Compare ML models with surrogate modelling frameworks including Graph Neural Operators.
• Evaluate model performance to reduce computational costs while maintaining accuracy.

Skills

Python

C++

Git

HPC clusters

Machine Learning

Data analysis

AI concepts

Communication

Education

Master’s degree in Coastal Ocean Modelling

PhD in Machine Learning or related field

Tools

Git

Python

C++

Job description

Analytics and Modeling Intern - Coastal Flood

London, United Kingdom

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving 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. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action— enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our 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.

Applications for this position will be accepted from 30 October through 13 November. We encourage interested candidates to apply early to ensure full consideration.

Skills and Competencies

• Experience working with high-performance computing clusters in a Linux environment and using version control software such as Git
• Strong programming skills in scientific and analytical languages such as Python and C++
• Experience with numerical models for ocean or wave modelling, or statistical modelling approaches
• Experience handling and analysing large datasets
• Familiarity with state-of-the-art machine learning methods such as Graph Neural Networks (GNNs) and Fourier Neural Operators (FNOs)
• Familiarity with model performance evaluation and model inter-comparison methods
• Strong analytical skills, with the ability to interpret results and communicate insights effectively
• 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

• Currently pursuing a Master’s degree or PhD in Coastal Ocean Modelling, Machine Learning, or a related field
• Ability to complete a 4‑month internship starting March 2027

Responsibilities

Support the development and evaluation of machine learning and surrogate models to improve the efficiency and accuracy of coastal flood risk modelling.

• Characterize key coastal flooding dynamics, including storm surge, waves and overland inundation, to identify the most relevant predictors and physical processes to capture
• Enhance existing machine learning models for processes relevant to coastal risk
• Explore machine learning methods (i.e. mSWE-GNN) to improve the representation of variability and extreme coastal flooding dynamics
• Compare machine learning models with alternative surrogate modelling frameworks, including Graph Neural Operators
• Evaluate model performance in reducing the computational cost associated with traditional numerical modelling while maintaining a high level of accuracy

About the Team

Our Model Development team is responsible for developing mathematical models and information to assess the financial impact of natural hazards. We are a multidisciplinary team of scientists and engineers, combining numerical, statistical, and data‑driven approaches to model damages caused by tropical storms, extra‑tropical storms, thunderstorms, coastal and freshwater floods, and tsunamis.
By joining our team, you will be part of exciting work within the Coastal Flood Risk team, which focuses on modelling coastal and offshore perils, including storm surge, offshore, nearshore and overland waves, wave setup, and overland inundation.

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.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.