At a Glance
- Tasks: Transform weather data into strategic insights for trading decisions.
- Company: Join RWE Supply & Trading, a leader in energy markets.
- Benefits: Competitive pay, inclusive culture, and growth opportunities.
- Other info: Collaborative team environment with a focus on innovation.
- Why this job: Make a real impact on energy transition with your weather expertise.
- Qualifications: Background in meteorology, strong data skills, and Python proficiency.
The predicted salary is between 50000 - 70000 £ per year.
RWE Supply & Trading GmbH
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? At RWE Supply & Trading, you’ll be at the heart of an international team of meteorologists and data experts, helping 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’ll thrive in a high‑paced environment with direct influence – your weather assessments will be used immediately to guide our trading positions. Plus, you’ll have the freedom and support to deliver goal‑driven solutions, backed by a passionate team.
Responsibilities
- 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.
- Proficient 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.
Your 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.
Weather Data Scientist d/f/m employer: RWE
RWE is an excellent employer, offering a dynamic work environment at the Little Barford Power Station where collaboration and proactive engagement are key. Employees benefit from a competitive salary, comprehensive pension scheme, and ample training opportunities for personal and professional growth, all within a supportive culture that values teamwork and innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Weather Data Scientist d/f/m
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We think you need these skills to ace Weather Data Scientist d/f/m
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at RWE, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at RWE. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at RWE
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
