Senior Forecasting Data Scientist - Energy Markets

Location: Rotterdam Region, Netherlands (Hybrid)

Important Requirements

This role is specifically targeted at candidates who:

• Are professionally fluent or native Dutch speakers.
• Are already based in the Netherlands and able to commute to the Rotterdam area on a regular basis.
• Have experience within the energy, power, utilities, renewable energy, or energy trading sector.

Candidates without Dutch language proficiency or relevant energy market exposure are unlikely to be successful for this opportunity.

About the Role

An innovative company operating within the energy sector is seeking a Senior Forecasting Data Scientist to develop and enhance forecasting models that support critical commercial and operational decision-making.

You will own the entire forecasting lifecycle, from data ingestion and feature engineering through to production deployment, monitoring, and continuous improvement. Your models will directly influence optimization, trading decisions, and the management of distributed energy assets.

This is not a traditional analytics role. The successful candidate will combine strong quantitative capabilities with a commercial mindset and an understanding of how forecasting impacts business performance.

Responsibilities

• Build and maintain advanced time-series forecasting models.
• Develop probabilistic forecasts across multiple forecasting horizons.
• Analyse complex relationships between market, operational, and external data sources.
• Work with weather, consumption, production, telemetry, and market datasets.
• Deploy machine learning models into production environments.
• Implement model monitoring, validation frameworks, automated testing, and drift detection.
• Continuously improve forecasting performance and business outcomes.
• Collaborate closely with quantitative, analytical, and commercial stakeholders.
• Support the ongoing evolution of forecasting methodologies as market conditions change.

Required Experience

• Master's or PhD in a quantitative discipline such as Mathematics, Statistics, Econometrics, Physics, Data Science, or similar.
• 3-5+ years of experience developing, deploying, and maintaining forecasting models in production.
• Strong expertise in:
  • Time-series forecasting
  • Probabilistic forecasting
  • Quantile regression
  • Model calibration
  • Statistical model evaluation
• Strong Python development skills.
• Experience with modern machine learning and data science tooling.
• Experience with:
  • Docker
  • CI/CD pipelines
  • Automated testing
  • Monitoring and MLOps practices
• Excellent communication skills and a proactive, ownership-driven mindset.

Highly Desirable

• Experience forecasting energy demand, generation, pricing, or related market behaviour.
• Experience working within:
  • Energy Trading
  • Utilities
  • Renewable Energy
  • Power Markets
  • Commodity Trading
• Exposure to stochastic modelling, optimization, or scenario-based forecasting.
• Experience working in environments where forecasts directly impact commercial outcomes.