Data Scientist

Octave.energy; Brussel Hoofdstad; Hybride; EUR 70 000 - 110 000; Plein temps

Avantages offerts par ce poste

Hardware in the loop

Hybrid working (2–3 days in the office

Competitive salary package

Training budget & benefits

Résumé du poste

Octave.energy is seeking an experienced data scientist to build probabilistic forecasts of electricity consumption and on-site generation, and to convert them into dispatch decisions for batteries, PV, and EV charging. You will develop real-time control algorithms that stay stable in dynamic conditions and work with edge devices to deploy models into production.

You will close the loop by tracking forecast errors, retraining, and comparing actual savings to expectations, while collaborating with

Qualifications

• Strong foundation in mathematical optimization and ability to convert business objectives into formulations.
• Expertise in time series forecasting and statistical modelling.
• Experience with real-time control algorithms on edge devices (PID, MPC, etc.).
• Proven problem-solving skills in ambiguous situations.
• Ability to explain complex models and control decisions to non-technical audiences.
• Commercial judgement to balance optimal vs live solutions.
• Fluency in Python.
• Knowledge of energy systems: electricity markets, load forecasting, asset dispatch.
• Experience with AI coding.
• Experience with AWS.
• Proven track record shipping models and controllers into production with monitoring.
• Experience working with messy field data (gaps, drift, sensor conflicts).

Responsabilités

• Develop probabilistic forecasting of electricity consumption and on-site generation with uncertainty estimates.
• Turn forecasts into dispatch decisions for batteries, PV, and EV charging within constrained optimization.
• Implement real-time control logic on edge devices ensuring stability.
• Close the loop by tracking forecast error, retraining, and updating models.
• Collaborate with Research Manager and institutes on data science workstreams.

Connaissances

Mathematical optimization

Time series forecasting

Real-time control

Problem solving

Explain models

Commercial judgement

Python

Energy systems knowledge

AI coding

AWS

Production deployment

Data quality handling

Description du poste

Are you an experienced data scientist? Do you know how to create reliable predictions and optimal decisions based on complex and large datasets? Do you want to put your talent to use and contribute to the energy transition by building innovative energy management solutions?

What you'll work on

• Probabilistic forecasting of electricity consumption and on-site generation at client premises — not only point forecasts, but the uncertainty estimates the control layer needs to make defensible decisions.
• Turning forecasts into control actions: converting forecasts and price signals into dispatch decisions across our clients' assets — batteries, PV and EV charging — with a single objective, minimizing their energy bill. In practice this means formulating and solving a constrained optimisation problem over each site's tariff structure, capacity limits and asset behavior, and doing it well enough that the result holds up when the forecast turns out to be wrong.
• Real-time execution, including control logic running on edge devices, that stays stable when conditions deviate from plan.
• Closing the loop between prediction, decision and execution, so the system runs unattended and improves on its own operating history. In practice: tracking forecast error against realized load and generation to drive retraining; comparing the savings actually achieved against what the optimiser expected, and attributing the gap to the forecast, the formulation or the asset; and correcting our models of the assets themselves — round-trip efficiency, degradation, state-of-charge drift — against what the fleet really does.
• R&D delivery: work alongside our Research Manager and top tier Research institutes on the data science workstreams of our ongoing research projects.

What we're looking for

• Mathematical optimisation is essential for this role: linear and quadratic programming, mixed-integer formulations, and ideally stochastic programming. You should be comfortable moving from a business objective to a formulation, and from a formulation to something that solves reliably within an operational time budget.
• A strong foundation in machine learning, time series forecasting and statistical modelling.
• Practical experience with real-time control algorithms on edge devices — PID, rule-based supervisory control, MPC, or comparable approaches you have deployed and maintained in the field.
• A problem solver by instinct: you're comfortable being handed an ambiguous situation, working out what's actually going on, and deciding what to do about it.
• The ability to explain a complex model or control decision to a non-technical audience — colleagues in sales and operations, and clients who want to understand why their battery did what it did.
• Commercial judgement: you can tell the difference between the solution that is optimal on paper and the one that goes live this quarter and starts paying for itself.
• Fluency in Python.
• Working knowledge of energy systems: electricity markets, load forecasting, asset dispatch, balancing mechanisms.
• Experience with AI Coding.
• Experience with AWS.
• A track record with messy field data — gaps, drift, sensors that contradict one another.
• Experience shipping models and controllers into production systems that run unattended, with monitoring in place. Notebooks are where the work starts, not where it ends.

What's in it for you

• Hardware in the loop. Your algorithms don't stop at an API boundary. They move megawatts through equipment installed at real sites.
• A short feedback loop. Models go live, are measured against real financial outcomes, and get improved. You'll know within days whether an idea worked.
• Room to set the direction. The team is small enough that your decisions about modelling, tooling and control architecture become the way Octave.energy does it.
• A mission with urgency. A renewable grid runs on flexibility: shifting demand towards the hours when the wind blows and the sun shines. Batteries, PV and EV charging are the three levers we pull, and better forecasting and control get more out of each of them.

We also offer

• An attractive salary package
• Offices in Mechelen and Brussels
• Flexible hours and hybrid working (2–3 days in the office)
• A collaborative team with genuine room to learn and grow in a fast-growing cleantech scale-up
• An attractive benefits package: Car/mobility budget, hospitalization & group insurance, training budget, cafeteria plan with 13th-month optimization, €10/day of lunch vouchers, eco-cheques and extra benefits (e.g., gym subscription).

About Octave.energy

Founded in April 2020, Octave.energy is a Belgian cleantech company specialized in battery energy storage and energy management services for businesses. We have sold over 200 MWh of storage capacity and operate the largest fleet of behind-the-meter batteries in Belgium. Backed by private investors, imec, and the European Commission's EIC Accelerator, we work at the forefront of the energy transition.

Interested?