Foundation Scientist – Data Science for Simulation

Job summary

We’re looking for two exceptional Foundation Scientists – Data Sciencefor Simulation to help us make a difference to our planet.

As our Foundation Scientist – Data Science for Simulation, the job may be suitable for hybrid working, which is where an employee works part of the week in the office and part of the week from home. This is a voluntary, non-contractual arrangement and the location advertised will be your contractual place of work.

Our opportunity is full time, 37 hours per week, but we would also consider applicants wishing to work a minimum of 30 hours per week and we will also try our best to consider those intending to work a job share. Our people are at the heart of what we do and we'll do our best to agree a working pattern that works for everyone.

World changing work

From science to technology, from meteorology to management, and from planning to communication, our expertise helps us stand out as the authority on weather accuracy and climate prediction. We help individuals, industries and government to make better decisions to stay safe and thrive. This is the Met Office. This is who we are.

• We’re a force for good - focusing on our environmental and social impact
• We’re experts by nature - always learning and developing to do things better
• We live and breathe it - putting our purpose at the heart of decision-making
• We’re better together - understanding partnerships and inclusivity make us greater
• We keep evolving - pushing boundaries to make tomorrow better for our customers

Your world of expertise

You will support research and development in data science and machine learning for weather and climate modelling, bringing advanced computational methods to prediction, simulation and environmental insight. This will include contributing to the strategically important FastNet Machine Learning Weather Prediction (MLWP) model, which is helping to explore how machine learning can support future operational weather prediction capabilities. Working with experienced colleagues, you will apply data science and machine learning techniques to real-world weather and climate challenges, collaborating closely with internal and external partners including other National Meteorological Services, research institutions and commercial organisations. This role offers an excellent opportunity to develop scientific, technical and collaborative skills while helping to create innovative solutions for weather and climate applications.

Job description

• Support the scientific development and technical implementation of machine learning solutions for Earth system applications, with a focus on weather forecasting.
• Contribute to scientific coding, data preparation, analysis, and evaluation activities and apply good software and research practices, with support from colleagues.
• Contribute to reports, presentations, and other outputs to communicate findings.
• Work collaboratively with scientists, engineers, and partners across projects
• Learn and develop expertise in relevant scientific, technical, and operational methods.

Person specification

1. Lead Criteria: A degree or equivalent experience in a scientific or computational discipline such as mathematics, physics, computer science, data science, atmospheric science or a related subject, with evidence of applying scientific or analytical thinking to solve problems (We’re experts by nature).
2. Experience of programming, such as Python, and an ability to use code to explore, analyse or process scientific, technical or environmental data, with support where needed (We’re experts by nature).
3. An understanding of, or demonstrable interest in, machine learning, AI or data science methods, and how they can be applied to scientific problems (We’re experts by nature).
4. Ability to work collaboratively with others and communicate technical information clearly to colleagues with different areas of expertise (We’re better together).
5. Good organisational skills, with the ability to manage defined tasks, respond to priorities and deliver useful outputs to agreed timescales with appropriate support (We live and breathe it).
6. A willingness and ability to learn new scientific or technical skills, apply feedback and develop effective ways of working (We keep evolving).

The panel may perform a preliminary sift of the lead criteria as indicated above

Benefits

Alongside your salary of £28,600, Met Office contributes £8,285 towards you being a member of the Civil Service Defined Benefit Pension scheme. Find out what benefits a Civil Service Pension provides (opens in a new window).

Our work is life-changing, often life-saving and always life-enhancing. The Met Office is Great Place to Work UK certified. We are also featured on their ‘Best Workplaces in Tech’ 2023, 2024 and 2025 lists, as well as their ’54 Best Workplaces for Women’ 2023 list.

As our Foundation Scientist – Data Science for Simulation, your total reward package will be up to £40,524 annually, which includes:

• £28,600 base pay
• An outstanding Civil Service pension, with an average employer contribution of 28.97%
• Annual Leave starting at 27.5 days (plus Bank Holidays) rising to 32.5 days (plus Bank Holidays) after 5 years and option to buy or sell up to 5 days per year of annual leave

Things you need to know

Artificial intelligence

Artificial intelligence can be a useful tool to support your application, however, all examples and statements provided must be truthful, factually accurate and taken directly from your own experience. Where plagiarism has been identified (presenting the ideas and experiences of others, or generated by artificial intelligence, as your own) applications may be withdrawn and internal candidates may be subject to disciplinary action. Please see our candidate guidance (opens in a new window) for more information on appropriate and inappropriate use.

Selection process details

If you share our values, we’d love to hear from you! Click apply to begin your application. Please complete your career history and provide evidence against each of the essential criteria in the supporting statement questionnaire. We recommend candidates use the CARL method (Context, Action, Result and Learning) for presenting evidence of experience and skills.

Please note: We are currently recruiting for 2 roles which are being advertised at 2 levels (Foundation Scientist and Scientist). Those wishing to be considered at multiple levels should submit an application at each level.

Closing date 24/09/2026 at 23:59 with first stage interviews commencing from 12/10/2026. You will hear from us once the closing date has passed.

Using AI in your application

We welcome applications that use AI tools for support in drafting or refining, as long as they accurately reflect your own skills and experience. All hiring decisions at the Met Office are made by people, not AI. For more details, visit our approach to recruitment.

How we can help

If you have any questions or would like to discuss this opportunity further, please contac