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Posted 13 months ago

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Quantitative Developer / AI & Automation Specialist – Power Trading

București, RORemote

AI Summary

Develops AI and machine learning models for power trading, including price forecasting, automated bidding, and arbitrage, while deploying models in live environments and building risk and compliance dashboards.

About this role

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;

Skills

AirflowAzure MLAzure MS FabricBRMDAMDatabricksDbtGitIdMKubeflowLIMELSTMMLflowOPCOMPower BIPythonPyTorchREST APISHAPSIDCSparkSQLTransformer

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