JOB TITLE: Principal Data Scientist
LOCATION: Juno Beach, FL
SCHEDULE: Standard
DURATION: 12-Month Contract
PAY: Up to $86-91/hr
Job Responsibilities:
In this role, you will lead and support enterprise forecasting initiatives within the IT Forecasting team, focused on developing and deploying advanced forecasting solutions for Load, Solar, and Wind generation. Key responsibilities include:
- Leading multiple forecasting initiatives, including:
o Developing production forecasting models for Load generation
o Building Solar forecasting solutions using weather-driven variables
o Designing Wind generation forecasting models
o Supporting real-time forecasting needs for operational decision-making - Leading full model lifecycle delivery from concept through production deployment.
- Supporting critical forecasting needs for Energy Management (EMT), Power Marketing (PMI), and System Operations (SysOps FPL).
- Collaborating with business, operations, and engineering stakeholders to deliver forecasting solutions aligned with operational priorities.
Essential Duties and Job Functions:
- Lead end-to-end forecasting model development for Load, Solar, and Wind generation, from design through production deployment.
- Develop automated retraining, evaluation, and monitoring frameworks for forecasting models.
- Build scalable forecasting pipelines supporting both real-time and batch forecasting operations.
- Develop connectors for weather APIs and integrate external weather data into forecasting workflows.
- Integrate forecasting solutions with internal systems and AWS cloud infrastructure.
- Implement robust error handling, alerting mechanisms, and recovery procedures for production forecasting systems.
- Perform advanced feature engineering using weather variables and operational signals.
- Optimize forecasting models to meet operational accuracy requirements and time-sensitive delivery deadlines.
- Build interactive dashboards using Streamlit or similar tools to communicate forecasting outputs and model performance.
- Present forecasting insights and model results to stakeholders across operations, trading, and engineering teams.
- Participate actively in Agile delivery environments and scrum ceremonies.
- Maintain forecasting model versioning, production monitoring, and lifecycle maintenance.
Knowledge & Skills:
- Advanced Python proficiency with strong experience using pandas, numpy, scikit-learn, and statsmodels.
- Deep expertise in time-series forecasting techniques including ARIMA, SARIMAX, and gradient boosting methods.
- Strong understanding of production model deployment, monitoring, and maintenance practices.
- Experience integrating APIs and external weather data sources into automated pipelines.
- Working knowledge of AWS cloud services including EC2, S3, Lambda, and SageMaker.
- Strong SQL skills with experience querying and optimizing large-scale datasets.
- Experience building interactive dashboards using Streamlit, Plotly, or similar visualization tools.
- Strong feature engineering capability using weather data and domain-specific signals.
- Knowledge of model evaluation metrics including MAE, RMSE, and MAPE.
- Experience with Git and automated version control practices.
- Strong communication and collaboration skills across technical and business teams.
- Ability to manage competing priorities in a fast-paced operational environment.
Preferred Skills & Experience:
- Advanced feature engineering and probabilistic forecasting methods.
- Uncertainty quantification in forecasting models.
- Energy markets, renewable generation, or utility forecasting experience.
- Agile project delivery experience using Jira and Confluence.
Education & Experience:
- Advanced degree preferred in Data Science, Statistics, Mathematics, Computer Science, Engineering, or related quantitative field.
- Proven experience developing and deploying production-grade forecasting models.
- Demonstrated experience supporting operational forecasting in complex business environments.
- Experience building scalable machine learning pipelines from research through production deployment.
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