At a Glance
- Tasks: Own the full lifecycle of data science projects, from research to deployment.
- Company: Dynamic climate tech startup focused on decarbonised energy systems.
- Benefits: Competitive salary, equity options, hybrid work, and enhanced parental leave.
- Other info: Join a flat team that values your voice and offers rapid feedback.
- Why this job: Make a real impact on climate tech while working with cutting-edge machine learning.
- Qualifications: Experience in shipping products and building models from research to production.
The predicted salary is between 60000 - 120000 € per year.
About the role
We are hiring a data scientist who ships. You will own the full lifecycle of your work: from research and prototyping through to production deployment, monitoring, and iteration. You will build machine learning models that operate reliably at scale, controlling thousands of EV chargers, batteries, and heating systems. We use real-time market data and ML to shift energy consumption to times when it is cheaper and greener. This is 50/50 data science and production engineering. You will write clean Python code, deploy on cloud, and work in Docker. You will see your work used by real customers.
What we are looking for
- You have shipped a product or feature that customers actually used.
- You understand the commercial impact of your work, not just the technical metrics.
- You are comfortable with:
- Building models from research through to production
- Python and cloud infrastructure
- Time-series data and forecasting
- Taking ownership end-to-end
- Working in small, flat teams where everyone has a voice
- Energy background is not required. Shipping ability is.
- Seniority: 1–2 years onwards. The sweet spot is around 5 years, but it depends on what you have actually built.
About the company
30-person team, backed by top-tier VCs. Deliberately flat structure. They move fast, give feedback within 24 hours, and people respond well to the mission: building software infrastructure for decarbonised energy systems.
What is in it for you
- £60–120k salary + 50–60% equity
- Hybrid: 3 days/week in London office
- Enhanced parental leave, cycle-to-work scheme, bi-annual team retreats
- Meaningful work on climate tech
Interview process
- Initial chat with technical lead (30 min)
- Take-home technical task (reviewed by the team)
- Final interview with founders (in-person, London)
The screening question they care most about: Have you shipped a product? And what was the commercial impact?
How to apply
If you have built and shipped something, I would like to hear from you.
Data Scientist in London employer: Wave Group
Join a dynamic and innovative climate tech startup in London, where you'll have the opportunity to make a tangible impact on decarbonised energy systems. With a flat organisational structure and a strong focus on employee feedback, we offer a collaborative work culture that values your contributions and encourages growth through meaningful projects. Enjoy competitive salaries, equity options, and a hybrid working model that promotes work-life balance while being part of a passionate team dedicated to sustainability.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in London
✨Tip Number 1
Get ready to talk about your projects! When you land that interview, be prepared to dive deep into the products or features you've shipped. Highlight the commercial impact of your work, not just the techy bits. We want to see how your contributions made a difference!
✨Tip Number 2
Practice makes perfect! Before your interviews, run through common data science scenarios and be ready to discuss your approach to building models from scratch. We suggest doing mock interviews with friends or using online platforms to sharpen your skills.
✨Tip Number 3
Show off your coding chops! Since you'll be writing clean Python code, brush up on your coding skills and be ready to demonstrate them. We recommend working on small projects or contributing to open-source to keep your skills fresh and relevant.
✨Tip Number 4
Don’t forget to network! Connect with people in the industry, attend meetups, and engage with communities online. We often share job openings on our website, so keep an eye out for opportunities that match your skills and interests!
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Show Off Your Shipping Skills:Make sure to highlight any products or features you've shipped that customers actually used. We want to see your impact, so don’t just list your technical skills—tell us how your work made a difference!
Keep It Clean and Concise:When writing your application, keep it clear and to the point. We appreciate straightforward communication, so avoid jargon and fluff. Let your passion for data science and production engineering shine through!
Tailor Your Application:Take a moment to tailor your application to our specific role. Mention your experience with Python, cloud infrastructure, and any relevant projects. We love seeing how your background aligns with what we do at StudySmarter!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you’ve built!
How to prepare for a job interview at Wave Group
✨Showcase Your Shipping Experience
Make sure to highlight any products or features you've shipped in your previous roles. Be ready to discuss the commercial impact of your work, as this is a key focus for the company. Prepare specific examples that demonstrate how your contributions made a difference.
✨Brush Up on Python and Cloud Skills
Since the role involves writing clean Python code and deploying on cloud infrastructure, it’s essential to be comfortable with these technologies. Review your past projects and be prepared to discuss how you’ve used Python and cloud services in your work, especially in production environments.
✨Understand Time-Series Data
Given the focus on time-series data and forecasting, make sure you can talk about your experience with these concepts. Brush up on relevant techniques and be ready to explain how you've applied them in real-world scenarios, particularly in relation to energy consumption or similar fields.
✨Embrace the Flat Team Structure
This company values a flat team structure where everyone has a voice. Be prepared to discuss how you thrive in collaborative environments and how you contribute to team dynamics. Share examples of how you’ve taken ownership of projects and worked effectively within small teams.
