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;