Senior Data Scientist

⚡️ 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-driven at core. 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 Senior Data Scientist to join us! 

👩‍💻 About The Role:

As a Senior Data Scientist, you will shape the foundation of Flower’s short-term forecasting capabilities - powering the models that directly drive our daily trading decisions. You will be part of a small, highly skilled team operating at the intersection of data science, energy systems, and close-to-real-time market dynamics.

You will own the full lifecycle of your models - from idea to production - working closely with Data Engineers, Machine Learning Engineers, and Energy Market Experts to ensure our forecasting stack runs smoothly and is continuously improving. This is a hands-on role focussed on time-series modelling, rapid experimentation, and the ability to translate data into high-impact operational decisions.

What You’ll Do:

• Build & maintain short term operational forecasting models for energy volumes & prices that drive our trading decisions on a day-to-day basis
  

• Build time series models to understand and explain recurring patterns across different measurements, products and regions to distill signals as features for your next model
  

• Prototype quickly: iterate on simple models, validate rigorously, and scale what works in a dynamic market environment
  

• Own the full model lifecycle: EDA, feature engineering, model development, validation, deployment and continuous evaluation, supported by our team of DEs, MLEs & Energy Market Experts
  

• Write your models in Python, version your code in Git, use CI/CD to ensure full reproducibility
  

• Partner with DEs to evaluate and integrate new data sources (weather, grid conditions, market signals)
  

• Collaborate & mentor across other data scientists, quants and engineers

Who You Are:

• Master’s or PhD in Statistics, Machine Learning, Computer Science, Industrial Engineering, Applied Mathematics, Engineering Physics, or a related quantitative field

• 5+ years building and deploying time-series prediction models in production using machine learning or classical methods

• Strong command of Python and no stranger to the command line; comfortable writing clean, maintainable, production-ready code

• Deep understanding of time-series forecasting and real-world modeling challenges

• Prior experience in energy markets or power systems

• Strong mentorship and coaching skills

• Highly driven by our mission and your impact, yet humble enough to know we are all always learning

• Eagerness to apply yourself in a mostly automated trading floor environment

• Thrive in a fast-moving environment and adapt models as markets evolve
  

📍 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 over 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 Talent Partner, Head of Predictions and Optimization, the Team, VP of Engineering and VP of Product.

We look forward to hearing from you!

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