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. 

Skills and Competencies

• Scientific background in mathematics, physics, engineering, earth sciences, or a related discipline, with an interest in weather‑related risk modelling
• Working knowledge of AI methods and hands‑on experience with data‑driven approaches
• Demonstrated programming skills in R, Python, or another programming language used for scientific computing
• Strong written and verbal communication skills, with the ability to present scientific research clearly and work effectively as part of a team
• Knowledge of hydrology and hydrologic modelling is preferred
• Advanced programming skills, including experience with GPU‑accelerated computing, are preferred
• Basic understanding of artificial intelligence concepts, with curiosity and enthusiasm for learning how AI tools can be used to improve processes and drive efficiency
• Interest in exploring AI systems and a willingness to develop awareness of responsible AI practices, including risk management and ethical use

Education

• Currently pursuing a degree in Mathematics, Physics, Engineering, Earth Sciences, Computer Science, or a related quantitative field

Responsibilities
The objective of this internship is to conduct applied research on AI based tools to model riverine and runoff processes, with the aim of improving flood model accuracy and efficiency.

Key responsibilities include:

• Conducting scientific literature reviews and sharing findings with the wider team
• Manipulating and analysing flood modelling datasets
• Prototyping, experimenting with, and evaluating modelling approaches at the forefront of scientific research

About the team
The Moody’s RMS Flood Development team brings together leading scientists to develop mathematical models that predict the distribution of potential damage resulting from natural hazards such as tropical storms, extra‑tropical storms, thunderstorms, storm surges, and fluvial flooding. These models are built using a combination of observed data, reanalysis data, numerical simulations, statistical models, and data assimilation techniques.

Within the Model Development department, the Flood team focuses on the development of high‑resolution, large‑scale hydrologic and hydraulic models to assess flood risk. The modelling work spans the full workflow, from hazard modelling through to loss modelling. The team operates within an engaged, collaborative working environment with a strong scientific and technological culture.

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.