Quantitative Developer

2 days ago

Bucharest, Bucureşti, Romania Sales Consulting Full time 60,000 - 120,000 per year

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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