Senior Data Scientist: Optimization gesucht in Berlin

• Create the high-level optimization frameworks (MILP, NLP, or Stochastic Programming) to manage residential energy flows across heat pumps, thermal storage, EVs, and batteries.
• Design and tune closed-loop control strategies to ensure system stability, robustness against model/reality mismatch, and seamless integration of high-level optimization with devices constraints.
• Utilize Stochastic & Learning-Based Control (e.g. Markov Decision Processes (MDPs), Reinforcement Learning, or Model Predictive Control (MPC) to handle the uncertainty of weather, prices, and human behavior.
• Develop ML models that respect real-world constraints. You ensure our algorithms "understand" the thermal inertia of a building or the degradation curves of a lithium-ion battery.
• Build high-fidelity simulations to validate algorithm performance against historical data before deploying code to edge devices and cloud environments.
• You don't just write formulas; you architect and implement complex models from scratch in Python, ensuring they are robust enough to run in a cloud-to-edge environment.
• Act as a senior voice in technical sessions. You will mentor junior team members and help navigate complex problem-solving and define the algorithmic requirements that guide our product roadmap.
• Work closely with Energy Engineers and Backend Developers to translate math into reliable, production-grade services that save customers money and CO2.

We know that nobody fits a job description 100%. If you see yourself in most of these points and are passionate about our mission, we'd love to hear from you!

• You are deeply familiar with mathematical optimization. You have hands-on experience with solvers for MILP, NLP, or MINLP (e.g., CasADi, Gurobi, Pyomo).
• You have in-depth statistical knowledge and experience in time-series forecasting, specifically handling uncertainty through stochastic modeling.
• You are proficient in Python and can design complex model architectures from the ground up, keeping "the big picture" (end-to-end thinking) in mind.
• You enjoy the "messy" reality of hardware. You are eager to learn the specifics of heat storage, hydraulic balancing, and electrical constraints to ensure your code works in the real world.
• You can explain the "Why" behind a complex stochastic model to a non-technical stakeholder and lead a brainstorming session on system architecture with ease.
• Bonus Points: You bring experience in energy usage prediction, Reinforcement Learning, IoT/Edge deployments, or energy management systems (EMS)-a plus, but not a must., You'll join a motivated, open-minded, and dynamic team passionate about driving the energy transition forward. We believe this mission can only succeed together.