Job Summary (List Format) Senior Data Scientist Load & Renewable Generation Forecasting
- Lead the development, enhancement, and productionization of forecasting models for Wind, Solar, and Load across NextEra Energy operations, with primary focus on Wind generation.
- Independently design, implement, validate, and optimize advanced statistical and machine-learning forecasting solutions from data exploration through deployment and ongoing monitoring.
- Analyze and optimize the use of multiple weather and Numerical Weather Prediction (NWP) providers, comparing their accuracy, coverage, latency, and reliability to maximize forecast performance and resiliency.
- Conduct feature engineering, model selection, and benchmarking to improve forecasting accuracy across diverse sites, horizons, seasons, and operational scenarios.
- Investigate forecast errors, identify root causes (weather, data quality, operational factors), and implement corrective actions.
- Integrate and analyze data from weather APIs, SCADA/telemetry, historical generation, and external sources to inform and improve forecasting models.
- Apply domain knowledge in meteorology, renewable energy (wind/solar), and electric load to enhance model relevance and accuracy.
- Monitor and evaluate forecast performance using metrics such as MAE, RMSE, bias, skill scores, and probabilistic measures.
- Develop and maintain data pipelines, connectors, and scalable batch & real-time forecasting workflows.
- Collaborate with data engineering, DevOps, and business stakeholders to deploy, maintain, and support forecasting applications in production environments.
- Build dashboards and analytical tools for communicating forecast performance and operational impacts.
- Ensure robust production support, including logging, alerting, diagnostics, and recovery procedures for forecasting solutions.
- Maintain clear model documentation, configuration management, version control, and software development best practices.
- Stay current with advancements in forecasting, machine learning, and renewable energy analytics; mentor less-experienced data scientists as needed.
- Prefer candidates with direct experience in utility-scale wind forecasting, energy market operations, SCADA telemetry, and benchmarking against commercial forecast vendors.