Data Science & Machine Learning Engineer

Job Summary (List Format) – Data Science & Machine Learning Engineer (NextEra Energy)

• Apply advanced data science and machine learning techniques to power commodity trading and analytics, with a strong focus on energy, power, and commodities markets.
• Leverage expertise in Python (pandas, NumPy, scikit-learn, PyTorch, TensorFlow) and SQL for data analysis, modeling, and deployment.
• Deploy production-grade ML and analytics systems on cloud platforms (AWS, Azure, or GCP).
• Utilize strong foundations in statistics, linear algebra, and optimization for model development and quantitative analysis.
• Develop and implement supervised, unsupervised, and reinforcement learning models for market forecasting and optimization.
• Fine-tune and evaluate large language models (LLMs) and build Retrieval-Augmented Generation (RAG) pipelines for automating market reports and trade rationale summaries.
• Build and manage agentic AI frameworks (LangChain, LlamaIndex, CrewAI) for autonomous data gathering, analysis, and trading decision support.
• Design and implement intelligent trading assistants or agent frameworks that monitor, forecast, and act on real-time market data.
• Develop and optimize time series models (ARIMA, Prophet, LSTM, XGBoost) for price, load, and renewable generation forecasting.
• Conduct scenario modeling, stochastic simulations, Monte Carlo analysis, and Value at Risk (VaR) assessments for trading and risk management.
• Integrate weather, grid, and market data into predictive and trading systems.
• Build robust data infrastructure including ETL/ELT pipelines, data warehousing (DataBricks, Snowflake), and vector database solutions.
• Ensure data governance, security, versioning, and compliance with industry regulations.
• Create dashboards and visual analytics (Power BI, Tableau, Plotly) to communicate trading performance, market exposure, and forecast accuracy.
• Translate complex technical findings into clear narratives and actionable insights for traders and business executives.
• Collaborate closely with trading, analytics, and engineering teams to deliver innovative solutions for power commodity markets.

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