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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

8Open Positions

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Model Development Intern - Winter Hazard

Moody's Corporation
Found 1 month ago
Location
London, United Kingdom
Duration (Months)
4 Months
Time
Not disclosed
Work Mode
On-site
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • Master
  • PhD

Skills & Qualifications

Technical Skills

  • Python
  • R
  • Julia
  • Linux/Unix
  • GitHub
  • ERA5
  • NARR

Soft Skills

  • Self motivated
  • proactive
  • able to work effectively both independently and as part of a team
  • curiosity
  • enthusiasm

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. 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.

Requirements

  • Proven ability to clean, process, and analyse large and complex datasets
  • Strong mathematical and statistical foundations
  • Solid programming skills in scientific languages (e.g., Python, R, Julia)
  • Good working knowledge of Linux/Unix environments and experience using version control tools such as GitHub
  • Experience reviewing and synthesising scientific or technical literature
  • Deep understanding of synoptic, mesoscale, or boundary layer meteorology (or wind engineering) preferred
  • Experience working with large scale meteorological datasets (e.g., ISD, ASOS/METAR, SPC severe weather reports) preferred
  • Familiarity with large scale modelled/reanalysis datasets (e.g., ERA5, NARR) preferred
  • Experience processing and visualising large spatial datasets preferred
  • Some knowledge of tail events and extreme value statistics preferred
  • Ability to communicate analytical results and insights clearly
  • Self motivated, proactive, and able to work effectively both independently and as part of a team
  • 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 exploring AI systems and a willingness to develop awareness of responsible AI practices, including risk management and ethical use

Related Field

  • AI & Machine Learning

Related Subfield

  • Applied Machine Learning

Languages

  • English

Nice to Haves

  • Deep understanding of synoptic, mesoscale, or boundary layer meteorology (or wind engineering)
  • Experience working with large scale meteorological datasets (e.g., ISD, ASOS/METAR, SPC severe weather reports)
  • Familiarity with large scale modelled/reanalysis datasets (e.g., ERA5, NARR)
  • Experience processing and visualising large spatial datasets
  • Some knowledge of tail events and extreme value statistics
▶Apply Now

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