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;
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 ...
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;
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