Analytics and Modeling Intern - Coastal Flood

Moody's; Greater London; On-site; GBP 20,000 - 27,000; Full time

Job summary

Moody's is seeking an internship candidate to support the development and evaluation of machine learning and surrogate models for coastal flood risk. You will work on coastal flooding dynamics, waves, and surge, collaborating with a multidisciplinary team.

The role focuses on improving ML models, exploring methods like Graph Neural Networks, and evaluating performance while managing computational costs. A Masters/PhD track is preferred and an internship begins March 2027 in the UK.

Qualifications

• Experience with HPC, Linux, and Git version control.
• Proficient in Python and C++ for scientific computing.
• Background in ocean/wave or statistical modelling is ideal.
• Experience handling large datasets and ML workflows.
• Familiarity with GNNs and Fourier Neural Operators (FNOs).
• Strong analytic and communication skills for insights.
• Demonstrated AI capabilities with ethical awareness.

Responsibilities

• Support development and evaluation of ML and surrogate models for coastal flood risk.
• Characterize coastal dynamics to identify key predictors and processes.
• Improve ML models for coastal risk and variability representation.
• Compare ML with surrogate frameworks and assess computational cost reductions.

Skills

HPC on Linux

Python

C++

Ocean modelling

Data analysis

GNNs

FNOs

Model evaluation

Analytical skills

AI implementation

Ethical AI

AI risk awareness

Education

Masters/PhD in Coastal Ocean Modelling or ML

Internship readiness (4 months starting March 2027)

Tools

Git

Job description

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.

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.