Principal Data Scientist - Load & Renewable Generation Forecasting

Locals profiles Required

Position Specific Description

The client is seeking a Principal Data Scientist to lead the development and production deployment of advanced forecasting models for Load, Solar, and Wind generation. 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

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)

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