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- Tasks: Lead your own data science project, enhancing weather data cleaning systems.
- Company: Join Vaisala, a global leader in measurement instruments and sustainable growth.
- Benefits: Gain hands-on experience, training sessions, and build a valuable professional network.
- Why this job: Make a real impact on weather risk management while developing your skills.
- Qualifications: Knowledge of meteorological datasets and proficiency in Python required.
- Other info: Dynamic office environment with excellent career growth opportunities.
The predicted salary is between 500 - 1500 £ per month.
Location: Harpenden, GB
Are you ready to take a Giant Leap? We’re looking for a Data Scientist Trainee for our Giant Leap program – a project-based internship in our Harpenden Office, UK. You will join our Vaisala Xweather team specialised in Finance and Insurance to enhance our Weather Data Cleaning Systems. This position is central to our operations, focusing on the creation and maintenance of high-quality datasets used by the weather risk management trading community. As a Giant Leaper, you will get your own project to lead for three months, starting in June.
Vaisala is a global leader in measurement instruments and intelligence helping industries, nations, people, and the planet to thrive. From predicting hurricanes to optimizing renewable energy production, our technology is used where it matters the most – from data centers, windfarms and laboratories to airports, the Arctic and even the surface of Mars. Our team of over 2,400 experts and 59 nationalities around the world is committed to taking every measure for the planet. Driven by our shared purpose, curiosity, and pioneering spirit, we stay ahead and make a difference.
Giant Leap is a unique opportunity for you to be the project manager of your own project, with the support of your teammates and project supervisor. Every year, these projects are carefully selected by our leadership teams, meaning that you get to work on real‑life questions that are important for us as a company. We invest in your growth with training sessions throughout the summer. Along with lessons from your own field and work life in general, you have a chance to learn, for instance, presentation skills, project management and problem solving. Connections built with fellow Giant Leapers, Vaisala’s brilliant experts and our leadership form an invaluable network for your career. Many of our former Giant Leapers have also gone on to build impressive careers at Vaisala after the program.
What will your summer look like? As a Junior Data Scientist trainee or a Meteorologist with significant Data Scientist experience trainee, you will help in advancing our applied machine learning capabilities to clean Historical Weather Data. You will focus on exploring and developing new features, testing a variety of modeling approaches, and supporting innovation in how we use supervised learning for complex time‑series and structured data challenges.
Key Responsibilities- Develop, improve and automate Data Cleaning Techniques, ensuring high accuracy and reliability.
- Experiment with a range of modeling techniques for the various weather variables: temperature, rain, wind, etc.
- Collaborate with software developers to integrate promising approaches into larger workflows.
- Automate clients’ data cleaning techniques used as an input to ML models.
The role will be predominantly office based.
What kind of skillset are we looking for?- Knowledge of meteorological datasets
- Hands‑on experience with machine learning libraries (scikit‑learn, XGBoost, PyTorch, TensorFlow, or similar).
- Familiarity with statistical methods.
- Proficiency in Python, with strong analytical and data manipulation skills.
- Familiarity with software development, ideally in C#.
- Excellent communication skills for liaising with internal teams and external stakeholders.
- While the core modeling is in Python, you will need to integrate your Python models/APIs with existing C#/.Net applications.
Are you ready to take a Giant Leap? Please apply by February 8, 2026, and include your CV. We’d also love to hear what inspired you to apply for this role and to Vaisala in a brief cover letter. If you want to know more, feel free to reach out to the hiring manager / project supervisor Michael Moreno via email michael.moreno@vaisala.com. Please note that applications sent via email cannot be processed due to privacy reasons. Kindly note that we are not able to provide support in relocation or work permit‑related applications.
Giant Leap Trainee, Data Scientist employer: Vaisala
Contact Detail:
Vaisala Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Giant Leap Trainee, Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current or former Giant Leapers on LinkedIn. Ask them about their experiences and any tips they might have for you. Building connections can give you insider info and make you stand out!
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Make sure you can talk confidently about machine learning libraries and data cleaning techniques. We want to see your passion and knowledge shine through!
✨Tip Number 3
Show us your enthusiasm! When you get the chance to chat with us, share what excites you about the role and how you can contribute to our team. A genuine interest can really set you apart from other candidates.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the Vaisala family. Let’s take that Giant Leap together!
We think you need these skills to ace Giant Leap Trainee, Data Scientist
Some tips for your application 🫡
Craft a Stellar CV: Your CV is your first impression, so make it count! Highlight your relevant skills and experiences, especially those related to data science and machine learning. Keep it clear and concise, and don’t forget to tailor it to the Giant Leap Trainee role.
Write a Compelling Cover Letter: This is your chance to show us your personality and passion! Share what inspired you to apply for this role and why you want to be part of Vaisala. Make it personal and connect your experiences to the responsibilities of the position.
Showcase Your Skills: Don’t just list your skills; demonstrate them! If you’ve worked with Python or machine learning libraries, mention specific projects or achievements. We love seeing how you’ve applied your knowledge in real-world scenarios.
Apply Through Our Website: Make sure to submit your application through our website. It’s the easiest way for us to keep track of your application and ensures that it gets to the right people. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Vaisala
✨Know Your Data
Make sure you brush up on your knowledge of meteorological datasets and machine learning libraries. Be ready to discuss how you've used tools like scikit-learn or TensorFlow in past projects, as this will show your practical experience and understanding of the role.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in data cleaning or modelling. Think of examples where you had to experiment with different techniques and how you approached problem-solving. This will demonstrate your analytical skills and creativity.
✨Communicate Effectively
Since you'll be liaising with internal teams and external stakeholders, practice explaining complex concepts in simple terms. You might even want to do a mock interview with a friend to refine your communication style and ensure you're clear and concise.
✨Ask Insightful Questions
At the end of the interview, have a few thoughtful questions ready about the Giant Leap programme or the Vaisala Xweather team. This shows your genuine interest in the role and helps you understand how you can contribute to their mission.
