Senior Data Scientist - Load & Renewable Generation Forecasting - #26-27215

• NextEra Energy is seeking a Senior Data Scientist to develop, improve, and support forecasting solutions for wind, solar, and electricity load.
• The role focuses primarily on wind generation forecasting and combines machine learning, weather analytics, data engineering, and production support.
• The candidate will build models, evaluate weather data providers, and improve forecast accuracy and reliability., * Develop, test, deploy, and improve wind, solar, and load forecasting models using weather data, historical generation/load, SCADA telemetry, statistical methods, and machine learning.
• Perform feature engineering, model validation, backtesting, benchmarking, and forecast-error analysis across sites, seasons, and forecast horizons.
• Evaluate weather and Numerical Weather Prediction (NWP) providers for accuracy, coverage, reliability, latency, and useful variables. Recommend provider selection, blending, and fallback approaches.
• Account for weather, equipment availability, curtailment, outages, and other operational factors affecting renewable generation and electricity demand.
• Integrate weather APIs, telemetry, databases, and external data feeds into scalable forecasting workflows.
• Monitor production forecasts for accuracy, data quality, model drift, and provider outages. Troubleshoot issues and implement alerts and recovery processes.
• Collaborate with data science, data engineering, DevOps, operations, and business teams to deploy and maintain forecasting applications.

• Advanced Python skills and experience with pandas, NumPy, scikit-learn, statsmodels, LightGBM, or XGBoost.
• Experience developing and deploying forecasting, time-series, or predictive models.
• Strong knowledge of feature engineering, regression, gradient boosting, ensemble methods, probabilistic forecasting, model validation, and backtesting.
• Experience analyzing weather APIs/NWP forecasts and integrating SCADA/telemetry, databases, or external data feeds.
• Strong SQL, data analysis, troubleshooting, and communication skills.
• Experience moving models from development into reliable production workflows.
• Working knowledge of AWS services such as EC2, S3, Lambda, Step Functions, CloudWatch, or SageMaker, or comparable cloud technologies.
• Familiarity with Git, testing, version control, and reproducible development practices.

Skills:

• Python - pandas, NumPy, scikit-learn, XGBoost/LightGBM.
• Time-Series Forecasting & Machine Learning - predictive modeling, regression, ensemble methods, model validation, and backtesting.
• Weather Data & NWP Analytics - weather APIs, Numerical Weather Prediction, and weather-provider performance analysis.
• Renewable Energy Forecasting - wind generation forecasting, solar forecasting, and electricity load forecasting.
• AWS & Data Engineering - AWS services, SQL, data pipelines, SCADA/telemetry integration, and production model deployment.

Education:

• Bachelor’s degree, Data Science, Information Technology, Computer Science, Engineering, or a related discipline. Equivalent relevant professional experience will be considered.