Model Development Intern - Catastrophe Risk

Moody's
London

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

  • General understanding of natural catastrophes and their impacts on communities and businesses
  • Strong verbal and written communication skills
  • Working knowledge of programming languages commonly used in model development (e.g., SQL, R, Python, Fortran)
  • Ability to work in a fast paced environment with flexibility in day to day tasks
  • Excellent time management and planning skills, with the ability to meet short deadlines
  • Strong critical thinking and problem solving skills, with high attention to detail
  • Ability to work both independently and collaboratively within a team
  • Familiarity with Linux/Unix environments
  • Familiarity with GitHub (preferred)
  • Familiarity with ArcGIS or QGIS (preferred)

Education

  • Currently studying towards an MSc or PhD in Meteorology, Geography, Geoscience, Mathematics, or related fields (including students transitioning between MSc and PhD programs)
  • Available for a 3-month internship starting in Summer 2026

Responsibilities

  • Monitor global catastrophic events, such as tropical cyclones, earthquakes, floods, and wildfires, and assess their potential impact by researching active events and supporting real time modelling workflows
  • Produce clear summaries, reports, and event updates that contribute to the generation of real time catastrophe modeling products
  • Assist in developing, testing, and improving code and processes used in real time operational systems during periods without active catastrophic events
  • Contribute to the annual Catastrophe Review report and support the maintenance of core operational workflows
  • Collaborate with the Event Response team to support project objectives and ongoing development initiatives

About the team
The Moody’s RMS Event Response team, based in London, is part of the Model Development group within the Models & Data business unit. The team builds custom solutions that enable customers to quantify the impact of real time catastrophic events, including tropical cyclones, earthquakes, floods, and wildfires.

The team works closely with model developers to adapt Moody’s RMS catastrophe models for real time applications, ensuring fast and accurate event insights. They also collaborate with model product management to ensure that solutions reflect the evolving needs of the insurance and reinsurance markets.

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.
Posted 2026-01-31

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