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New rolePosted 15 June 2026Springpod

Met Office Careers: Data Science and Meteorological Phenomenon

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The Met Office

Remote (UK)Virtual Experience

Role overview

About this role

Overview Weather plays a crucial part in our lives - but how can we understand it better? How does data science and the Met Office play their part? Join this Sprint with the Met Office, and use your skills to understand the relationships within data sets, and, with the help of expert professionals, explore how the Met Office uses data to understand our weather and its implications. In this Sprint, you’ll be supported by Damian Wilson, Head of Science Learning and Development at the Met Office. Damian will take you through some key aspects of the work of the Met Office, and guide you through a task that’ll show you key patterns and relationships within data. Plus, you’ll get a chance to hear more about data science and Damian’s journey in the sector and the different career pathways available! What’s Included This Sprint is a way for you to carry out a real-world task and will give you a taste of what a future career within the Met Office could look like. You’ll learn from your Met Office mentor through videos and compare your work with their model answers to refine your abilities even further.

Job details

Compensation

Unpaid opportunity

Location

Remote (UK)

Remote available

Posted

15 June 2026

Entry requirements

Requirements not available here

The employer hasn't published structured entry requirements through this listing. Check their application page for GCSEs, A-Levels, or any other entry criteria.

See entry requirements on employer listing

Remote (UK)

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Company

The Met Office

The Met Office hires students into technology-focused teams where software, data, infrastructure, product thinking, reliability, and user impact often matter.

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Role insight

Preparing for The Met Office

Good preparation includes project evidence, curiosity, debugging examples, teamwork, and being able to explain technical choices clearly.

  • Talk through one project in terms of problem, trade-offs, result, and what you would improve.
  • Be ready to explain code or data decisions without jargon.
  • Connect technical work to users, reliability, security, or business value.