DR We help large enterprises cut energy costs and valorize flexibility by steering their energy use in sync with market prices and renewable generation. We're hiring a Data Scientist to develop the forecasting, optimization, and control algorithms at the core of Companion's platform. energy connects the financial side of energy management (contracts, markets, risk) with the operational side (assets, processes, sites). We model complex energy contracts and flexible assets, forecast demand and production, and translate predictions into automated, second-by-second control decisions that move megawatts and money. Our software is used by large B2B enterprises and energy players to lower OPEX, maximize revenue, increase renewable usage, and manage risk.
See your work in production: Models you build get deployed and measured against real financial outcomes daily. Controllers you design steer real assets in real time.Join early, help shape the future: Small team, big impact. You'll shape Companion's data, ML, and control strategy.Control algorithms that translate forecasts and market signals into real-time asset dispatch decisions (battery steering, load shifting, balancing market participation), accounting for the inherent stochasticity of prices, generation, and demand.Closing the loop: connecting prediction, planning, and execution into systems that operate autonomously in a stochastic environment.
Strong foundation in machine learning, time series forecasting, and statistical modeling.Proficiency in Python and the standard data/scientific computing stack (pandas, NumPy/SciPy, scikit-learn, PyTorch or equivalent).Experience working with real-world, messy time series data.Pragmatic approach: you understand the difference between a theoretically optimal solution and one that ships and delivers value under real-world uncertainty.Intro call → technical case → follow-up conversations with the team and founders. We keep it simple and can move fast.
Tell us why this role excites you and share something relevant: a model you built, a control system you designed, a Kaggle notebook, or a project that shows how you approach data and engineering problems.