Data Scientist – Energy Forecasting & Optimization

You'll help shape the future of energy flexibility. As a Data Scientist, you develop forecasting and optimization models that make industrial and commercial energy systems smarter, greener, and more profitable — driving our Flex product for automated energy trading and intelligent control of distributed energy resources.

• Develop and improve optimization models for battery scheduling, EV charging and energy cost reduction
• Build forecasting models for consumption, PV generation, charging demand and market-related signals
• Apply statistical methods (time series analysis, regression, hypothesis testing) to analyze energy data
• Analyze operational and pilot project data to identify optimization opportunities
• Work with real customer systems, messy operational data and practical constraints such as runtime, reliability and cost
• Collaborate closely with engineers, product colleagues and energy experts to bring models into production
• Support sales with requirements analysis and system simulations

• Strong Python skills (Jupyter, Pandas, NumPy, SciPy, cvxpy) and experience connecting to diverse data sources (databases, REST APIs, file formats)
• Degree in a scientific or engineering discipline (e.g. electrical engineering, physics, mathematics, computer science, energy systems)
• Proven experience with convex optimization and mixed-integer linear programming (MILP)
• In-depth knowledge of electricity markets, especially spot market trading in Germany
• A pragmatic builder and analytical mindset: you care about shipping robust solutions, not just elegant models, and enjoy turning insights into interactive notebooks and visualizations
• Clear communication and ownership in a fast-moving, collaborative startup environment
• Fluent English (C1); German is a plus but not required — we value curiosity and willingness to learn over existing fluency
• Bonus: experience with commercial energy technology components (batteries, EV chargers, PV systems)

1. online Interview

2. Interview in Munich

(3. another additional interview)