Data Scientist

ppWe're hiring a Data Scientist to build the forecasting, optimization, and control algorithms at the core of Companion's platform. /ppModels that steer energy demand forecasting, market price prediction, and real-time asset control, driving decisions worth millions. /ppWe help large enterprises cut energy costs and valorize flexibility by steering their energy use in sync with market prices and renewable generation.br/We're hiring a Data Scientist to develop the forecasting, optimization, and control algorithms at the core of Companion's platform.br/You'll work on energy demand forecasting, market price prediction, and real-time asset control: models and algorithms that drive second-by-second decisions worth millions. /ph3About Companion.energy /h3pCompanion.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. /ph3Why Companion.energy? /h3ulliWork on hard problems: Real-time forecasting, optimization, and closed-loop control in complex, stochastic energy systems. Your models and controllers move megawatts. /liliSee 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. /liliJoin early, help shape the future: Small team, big impact. You'll shape Companion's data, ML, and control strategy. /liliA mission that matters: Better forecasting and smarter control accelerate the transition to a flexible, renewable grid. /li /ulh3What you'll work on /h3ulliForecasting models for energy demand, renewable production, and market prices
- including the uncertainty estimates that feed downstream control. /liliControl 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. /liliOptimization pipelines that schedule flexibility across portfolios of assets and markets under uncertainty. /liliClosing the loop: connecting prediction, planning, and execution into systems that operate autonomously in a stochastic environment. /li /ulh3What we are looking for /h3ulliStrong foundation in machine learning, time series forecasting, and statistical modeling. /liliExperience with control algorithms: model predictive control (MPC), stochastic optimal control, or similar approaches to real-time decision-making under uncertainty and constraints /liliExperience with short-term power or flexibility trading /liliProficiency in Python and the standard data/scientific computing stack (pandas, NumPy/SciPy, scikit-learn, PyTorch or equivalent). /liliExperience working with real-world, messy time series data. /liliComfort deploying models and control algorithms in production environments, not just notebooks. /liliInterest in or knowledge of energy systems: electricity markets, load forecasting, asset dispatch, balancing mechanisms, or related domains. /liliPragmatic approach: you understand the difference between a theoretically optimal solution and one that ships and delivers value under real-world uncertainty. /liliExperience with mathematical optimization (linear/quadratic programming, mixed-integer formulations, stochastic programming) is a strong plus. /li /ulh3How we hire /h3pIntro call
- technical case
- follow-up conversations with the team and founders.br/We keep it simple and can move fast. /p /p