Senior Data Scientist – Load & Renewable Generation Forecasting
Position Specific Description
The IT Forecasting team is seeking a Senior Data Scientist to develop, enhance, and productionize forecasting solutions supporting Wind, Solar, and Load forecasting across NextEra Energy operations.
The primary focus of this role will be Wind generation forecasting, while also providing technical support across Solar and Load forecasting initiatives.
This is a hands-on role combining forecasting, meteorology, renewable-energy analytics, machine learning, data engineering, and production support. The successful candidate will independently develop and improve forecasting models from data exploration and feature engineering through validation, deployment, monitoring, and ongoing optimization.
A key responsibility will be evaluating and optimizing the use of weather and Numerical Weather Prediction (NWP) providers. The candidate will compare provider accuracy, available variables, forecast horizons, geographic coverage, latency, reliability, and overlap between services to determine the most effective weather inputs for each forecasting application. This includes identifying where individual providers or weather features perform better under specific conditions and identifying opportunities to reduce unnecessary provider redundancy while maintaining forecast accuracy and resiliency.
The ideal candidate combines strong statistical and machine-learning skills with practical understanding of the meteorological, physical, and operational factors affecting renewable generation and electric demand.
The candidate should understand that observed generation and demand can be influenced by operational conditions in addition to weather and account for these factors when developing, training, and evaluating forecasting models.
Required Skills & Experience
- Advanced proficiency in Python and common data-science libraries such as pandas, NumPy, scikit-learn, statsmodels, LightGBM, XGBoost, or equivalent tools.
- Demonstrated experience developing and deploying forecasting, time-series, or predictive models.
- Strong knowledge of:
- Feature engineering
- Regression and time-series methods
- Gradient boosting
- Ensemble forecasting
- Probabilistic or quantile forecasting
- Model validation and backtesting
- Experience integrating and analyzing weather APIs, NWP forecasts, SCADA/telemetry, databases, and external data feeds.
- Ability to evaluate weather-provider performance and determine its impact on forecast accuracy.
- Strong SQL and data-analysis skills.
- Experience transitioning models from research and development into reliable production workflows.
- Working knowledge of AWS services such as EC2, S3, Lambda, ECS, Step Functions, CloudWatch, and SageMaker, or comparable cloud technologies.
- Experience with Git, version control, testing, and reproducible software-development practices.
- Strong troubleshooting, analytical, communication, and documentation skills.
- Ability to work independently while collaborating effectively with data scientists, data engineers, DevOps, operations, trading, and business stakeholders.
