Senior Data Scientist

Flower

Stockholm, Sweden

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.