Principal Data Scientist - Load & Renewable Generation Forecasting

Job Description:

Position Specific Description The IT Forecasting team is seeking a Principal Data Scientist to lead the development and production deployment of advanced forecasting models for Load, Solar, and Wind generation across NextEra Energy operations.

This role supports critical decision-making for Energy Management (EMT), Power Marketing (PMI), and System Operations (Sysops FPL).

This position will engage in end-to-end model development from conception through production deployment, including advanced feature engineering, weather data integration via APIs, model optimization, and performance monitoring.

The ideal candidate will design production-ready forecasting solutions integrated with internal systems, AWS cloud infrastructure, implementing robust error handling, alerting mechanisms, and recovery procedures.

The successful candidate should possess deep expertise in time-series forecasting, machine learning operations, and building scalable data pipelines.

They must demonstrate the ability to transform complex datasets into actionable forecasts that drive real-time operational decisions in the energy sector.

We are looking for someone who has a passion for solving challenging forecasting problems and can deliver production-grade solutions in a dynamic operational environment with stringent accuracy requirements and time-sensitive obligations.

Key Expectations:

Understands business priorities and takes ownership of the complete model lifecycle from development to production deployment

Demonstrates strong communication and collaboration skills working with trading, operations, and engineering teams

Works effectively within Agile frameworks and actively participates in scrum ceremonies

Deliver cost-effective, high-quality forecasting solutions that meet operational deadlines and accuracy standards Job Overview Job Duties & Responsibilities Model Development & Production:

Lead end-to-end forecasting model development for Load, Solar, and Wind from conception through production deployment Build automated retraining and evaluation frameworks with monitoring dashboards Data & Infrastructure: Develop data connectors for weather APIs and data warehouse systems Design scalable pipelines for real-time and batch forecasting operations Create interactive dashboards (Streamlit) and present insights to stakeholders

Must Have Skills: Required Skills & Experience: Python Expertise: Advanced proficiency in Python with extensive experience in data science libraries (pandas, numpy, scikit-learn, statsmodels)

Time-Series Forecasting: Proven track record developing and deploying production forecasting models (ARIMA, SARIMAX, gradient boosting methods) Production Deployment: Demonstrated experience taking models from research/development through production deployment with proper versioning, monitoring, and maintenance API Integration: Experience consuming and integrating weather APIs and external data sources into forecasting pipelines, with a strong background in data engineering Cloud & Infrastructure: Working knowledge of AWS services (EC2, S3, Lambda, SageMaker) and Infrastructure-as-Code practices Database Management: Proficiency with SQL databases and experience with large-scale data queries and optimization Dashboard Development: Experience building interactive dashboards using Streamlit, Plotly, or similar frameworks for stakeholder communication Preferred Skills & Experience:

Advanced feature engineering, uncertainty quantification, and probabilistic forecasting methods Energy markets and renewable generation forecasting domain expertise Agile project management (Jira, Confluence) Technical Competencies: Feature engineering with weather variables and domain-specific signals Model evaluation metrics (MAE, RMSE, MAPE) Automated data pipelines and version control (Git)