Responsabilities:

• Develop AI models for forecasting consumption and production, including renewables;
• Build predictive models for prices in DAM, IDM, and BRM markets;
• Forecast imbalances and associated costs using advanced ML techniques (LSTM, Transformer, regression);
• Design and implement automated bidding strategies in DAM and IDM;
• Develop arbitrage algorithms across OPCOM, BRM, and SIDC;
• Optimize revenues from batteries and storage through AI-driven models;
• Automate data pipelines for OPCOM, BRM, ENTSO-E, ANRE, and weather data;
• Apply feature engineering specific to energy trading (ramp rate, forecast error, imbalance cost);
• Deploy AI models in live trading environments with monitoring and recalibration;
• Implement MLOps practices using MLflow, Azure ML, Databricks;
• Create dashboards in Power BI showing forecasts vs. actuals, bidding recommendations, and risk metrics;
• Ensure compliance with ANRE, REMIT, GDPR through explainability (SHAP, LIME) and documentation;
• Provide audit-ready workflows with full reproducibility;
• Collaborate closely with traders to integrate AI models into decision-making;
• Conduct risk simulations and scenario analysis to support trading strategies;

Requirements:

• Machine Learning: advanced knowledge in supervised and unsupervised learning, time series modeling;
• Deep Learning: experience with LSTM, Transformer and CNN for sequential data;
• MLOps: use of platforms such as MLflow, Kubeflow, Azure ML for managing the model lifecycle;
• Data Engineering: skills in ETL, Airflow, Spark, dbt and SQL for efficient data processing;
• Programming: expertise in Python (pandas, scikit-learn, PyTorch) and version control with Git;
• Visualization: creation of interactive dashboards with Power BI;
• API & Integration: development and consumption of REST APIs, integration with OPCOM/BRM APIs;
• Model Explainability: use of SHAP and LIME techniques for AI model interpretation;
• Energy Trading: deep understanding of DAM, IDM, BRM and SIDC markets;
• Decision Optimization: development of algorithms for automated bidding, arbitrage and HFT strategies;
• Energy Forecasting: ability to build accurate models for price, imbalance and production forecasting;
• Risk Analysis: conducting simulations and scenarios for risk and cost estimation;
• Communication: ability to explain complex AI concepts to non-technical stakeholders;
• Collaboration: effective work with traders, IT, BI and operations teams;
• Strategic Thinking: aligning AI solutions with the commercial objectives of the department;
• Adaptability: ability to react quickly to market or regulatory changes;
• Professional Ethics: responsibility in the use of AI, with focus on transparency and fairness;
• Cloud & Infrastructure: experience with Azure MS Fabric for scalability;