Data Scientist

Companion.energy; Belgique; Hybride; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Companion.energy is hiring a Data Scientist to build forecasting, optimization, and control algorithms at the core of Companion's platform. You will develop models for energy demand, market prices, and real-time asset control, enabling decisions that affect megawatts and millions in value.

Join a small, impact-driven team shaping data, ML, and control strategy for a renewable-ready grid. Strong ML foundation, MPC or stochastic control experience, Python and the data stack, plus a pragmatic

Qualifications

• MSc/PhD in a quantitative field such as CS, math, statistics.
• Strong background in ML, forecasting, and optimization.
• Experience with real-time/production systems.
• Ability to deploy models to production.

Responsabilités

• Develop forecasting models for energy demand, production, and prices.
• Design and implement MPC or stochastic control for real-time dispatch.
• Build optimization pipelines for portfolios under uncertainty.
• Bridge prediction, planning, and execution in autonomous systems.

Connaissances

Machine learning

Time series

Statistical modeling

Python

Pandas

NumPy

SciPy

Scikit-learn

PyTorch

MPC

Formation

Master's degree in data science / statistics / maths

Outils

Docker

Git

SQL

Airflow

Description du poste

We're hiring a Data Scientist to build the forecasting, optimization, and control algorithms at the core of Companion's platform.

Models that steer energy demand forecasting, market price prediction, and real-time asset control, driving decisions worth millions.

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.
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.

About Companion.energy

Companion.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.

Why Companion.energy?

• Work on hard problems: Real-time forecasting, optimization, and closed-loop control in complex, stochastic energy systems. Your models and controllers move megawatts.
• 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.
• A mission that matters: Better forecasting and smarter control accelerate the transition to a flexible, renewable grid.

What you'll work on

• Forecasting models for energy demand, renewable production, and market prices - including the uncertainty estimates that feed downstream control.
• 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.
• Optimization pipelines that schedule flexibility across portfolios of assets and markets under uncertainty.
• Closing the loop: connecting prediction, planning, and execution into systems that operate autonomously in a stochastic environment.

What we are looking for

• Strong foundation in machine learning, time series forecasting, and statistical modeling.
• Experience with control algorithms: model predictive control (MPC), stochastic optimal control, or similar approaches to real-time decision-making under uncertainty and constraints
• Experience with short-term power or flexibility trading
• 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.
• Comfort deploying models and control algorithms in production environments, not just notebooks.
• Interest in or knowledge of energy systems: electricity markets, load forecasting, asset dispatch, balancing mechanisms, or related domains.
• Pragmatic approach: you understand the difference between a theoretically optimal solution and one that ships and delivers value under real-world uncertainty.
• Experience with mathematical optimization (linear/quadratic programming, mixed-integer formulations, stochastic programming) is a strong plus.

How we hire

Intro call - technical case - follow-up conversations with the team and founders.
We keep it simple and can move fast.