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Apply here: Data Scientist

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We’re looking for a Data Scientist to shape and build Skye key data capabilities like loads consumption forecasting, energy markets prediction, energy consumption optimization, and bidding strategies all across our energy products.

You will own the development of Skye platform intelligence and you will be involved in new product exploration projects. In addition, you will collaborate with the Product Team on shaping our data platform to turn raw telemetry into actionable intelligence.

This is a unique opportunity to join a fast-moving, VC-backed startup and make a significant impact on the product, culture, and business. We are now looking for exceptional talents to join our mission to make European industry global winners in the new energy system.

What we’re building

Skye is building the energy autopilot for industries.

Our platform connects industrial assets to energy markets — optimizing electricity use, providing balancing services (FCR/FRR), and automating trading.

To make that possible, we process large volumes of telemetry and market data in real time to which we need to add intelligence and analytical capabilities.

Our data stack powers:

• Real-time analytics and monitoring of industrial assets
• Forecasting and optimization models for power flexibility
• Automated market operations and insights for customers

What you’ll do

• Build, train, and deploy statistical and ML models that power core business decisions: from energy loads forecasting to market predictions.
• Design and operate simulation and optimization engines for energy market bidding, turning model outputs into automated, executable strategies.
• Research and prototype new modeling approaches, whether that's improving forecast accuracy, exploring new market signals, or validating entirely new product concepts.
• Collaborate closely with data engineering to shape ETL pipelines and define golden tables optimized for modeling and feature engineering.
• Build observability and monitoring layers around model performance, data drift, and prediction quality, ensuring reliability in production and market compliancy.