Data Science & Machine Learning Internship

⚡️ What We Do
Flower is Flexible Power. We are a next-gen energy company leveraging AI and machine learning to make renewable energy stable and always available – even when the sun isn’t shining and the wind isn’t blowing.

Through smart optimization and trading of energy assets like wind and solar farms, battery systems, and EV chargers, we make renewable energy reliable and predictable, leading the charge towards the energy system of tomorrow.

🌟 Who We Are
Tech company at heart – purpose in our DNA. Flower consists of a diverse group of innovative individuals with a strong desire to improve the state of the world.

At Flower, we believe trust, collaboration and diversity are essential to not only create an inclusive work environment, but also drive career growth. By embracing varying perspectives, we allow creativity and progress to flourish.

To accelerate towards our goal of becoming the pioneering force powering the energy system of tomorrow, we are now looking for a passionate and skilled intern in the Predictions & Asset Optimization Team for a paid summer internship.

This isn’t a coffee-fetching internship. You’ll be building, learning, and making things happen alongside a team that moves fast, thinks big, and genuinely enjoys the ride.

If you’re looking for the most impactful - and exciting - internship of the summer, you’ve just found it.

👩‍💻 About The Role:

You’ll work alongside a highly competent team which is redefining how energy systems operate. Expect real responsibility, steep learning curves, and the chance to contribute to something that truly matters.

You will be embedded with our Data Scientists and Machine Learning Engineers to help us produce the best AI wind power forecasts in Europe. You will take a deep look at complex weather and power data and perform temporal and geospatial analysis, as well as analysing historical error distributions to identify the biggest levers for wind power prediction performance. You will then yourself encode them as features and deploy these models to production.

What You’ll Do:

• Deep evaluation of different weather providers for our partners’ sites, including numerical and AI driven weather models

• Analyze historical error distributions to identify systematic patterns & zero in on the biggest performance uplift potential

• Lots and lots of visualizations across time & space to understand wind power and model behaviour across different weather, temporal and power regimes

• Derive specific improvements to our feature pipelines & models, backtest, retrain and redeploy

• Monitor your results and be proud of your impact in production

Who You Are:

• University studies in Data Science, Statistics, Mathematics, Applied Physics, Energy Engineering or related (quantitative) fields

• Currently in the final years of your academic journey (preferably in the last years of your Master’s), or recently graduated

• You’ve worked with Python before

• You are curious about energy transition

• Fluency in spoken and written English

• Eligible for work in Sweden

• You are based in Stockholm

• Available for work from June 8th, for about 8-10 weeks, full time (40 hours per week)

What’s in it for you:

• A paid internship

• A fast-moving, high-impact tech environment with a leading-edge tech stack

• Hands-on experience with AI, energy markets, and large-scale infrastructure

• A steep learning curve alongside top engineers and traders

• A diverse, international team and strong professional network

• Great office in central Stockholm (Slussen) with the best view in the city

• An in-office gym to kickstart your mornings or reset after a productive day

• A constantly stocked selection of snacks, coffee, and treats to keep your energy (and mood) high

📍 Location

Our beautiful office is located in the heart of Södermalm, just a short walk from Slussen subway station. We encourage in-office collaboration but support a hybrid work model.

✉️ Apply

Our corporate language is English, as we have about 30 nationalities in the office. We therefore appreciate it if you could submit your CV in English.

Throughout the recruitment process you will meet with the Hiring Manager, members of the team, and the Talent Partner.

We look forward to hearing from you!

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