Weather Data Scientist d/f/m

Weather Data Scientist d/f/m

Full-Time 50000 - 70000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Transform weather data into strategic insights for global energy trading.
  • Company: Join RWE Supply & Trading, a leader in energy transition.
  • Benefits: Competitive pay, inclusive culture, and growth opportunities.
  • Other info: Flexible work arrangements available; we value diverse perspectives.
  • Why this job: Make a real impact on energy markets with your weather expertise.
  • Qualifications: Background in meteorology, strong data skills, and Python proficiency.

The predicted salary is between 50000 - 70000 £ per year.

London, City of London, GB EC2R 8HP; Essen, NW, DE 45141.

RWE Supply & Trading Gmb H

To start as soon as possible, full time / part time, permanent.

About the role

Are you ready to turn weather insight into real trading impact?

As part of an international team of meteorologists and data experts, you will help shape decisions that power global energy markets.

This opportunity is about more than just analysis—it's about collaborating across disciplines, innovating, and transforming complex weather data into clear strategic advantages for our traders.

You will thrive in a high‑paced environment with direct influence—your weather assessments will be used immediately to guide our trading positions.

You’ll have the freedom and support to deliver goal‑driven solutions, backed by a passionate team.

  • Verify and evaluate weather model outputs, ensuring quality and relevance to trading decisions.
  • Visualise and translate complex weather information into actionable insights for trading teams.
  • Build bespoke tools and drive innovation in weather forecasting and analytical processes.
  • Establish, maintain, and optimise robust data pipelines.
  • Communicate technical findings in clear, engaging language to stakeholders, enabling confident action across the organisation.
  • Job requirements and experience
  • Academic or commercial background in weather science or meteorology.
  • Strong quantitative modelling skills, including handling large, complex datasets.
  • Proficiency in Python, SQL, and cloud computing platforms.
  • Familiarity with data visualisation platforms.
  • Curiosity‑driven approach—always seeking innovative solutions, whether independently or as part of a collaborative team.
  • Ability to take ownership, make informed decisions, and push projects forward with drive and accountability.
  • Collaborative spirit—sharing insights, supporting colleagues, and helping strengthen our collective trading performance.
  • Advantageous, but not essential
  • Experience in machine learning applications for weather or data science.
  • Understanding of, or interest in, global trading business dynamics.

What we value most is someone who continuously demonstrates courage, thrives to create impact, and seeks to build trusting, collaborative relationships.

If you do not yet display all of the skills listed above, we would still like to hear from you.

We also welcome applications from individuals who may not be able to commit to full‑time roles.

Finding the right person for the job is our top priority, and we are willing to explore flexible arrangements.

Benefits

  • The chance to make a tangible impact on key business decisions at the centre of Europe’s energy transition.
  • A multicultural, inclusive environment where diverse perspectives drive better outcomes.
  • Opportunities for continuous personal and professional development—grow your career as you innovate with us.
  • Competitive compensation and benefits packages.

We value diversity and therefore welcome all applications—regardless of gender, disability, nationality, ethnic and social origin, religion/belief, age, sexual orientation, and identity.

We are committed to equal employment opportunity and prohibit discrimination in hiring.

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Contact Details:

RWE AG Recruitment Team

We think you need these skills to ace Weather Data Scientist d/f/m

Weather Science
Meteorology
Quantitative Modelling
Data Handling
Python
SQL
Cloud Computing