Principal Data Scientist

Principal Data Scientist – Load & Renewable Generation Forecasting

Location: Juno Beach, FL

Job Description

We are seeking an experienced Principal Data Scientist to lead the development and production deployment of advanced forecasting models for load, solar, and wind generation .

The ideal candidate will have deep expertise in time-series forecasting, Python, machine learning, AWS, and production model deployment . This role will involve the complete model lifecycle, from model design and feature engineering through deployment, monitoring, optimization, and automated retraining.

Key Responsibilities

• Lead end-to-end development of forecasting models for load, solar, and wind generation .
• Develop and deploy production-ready time-series and machine learning models .
• Perform advanced feature engineering using weather data and other domain-specific variables .
• Integrate weather APIs and external data sources into forecasting pipelines.
• Build scalable automated pipelines for real-time and batch forecasting.
• Develop model validation, monitoring, retraining, and performance evaluation frameworks.
• Optimize forecasting accuracy using metrics such as MAE, RMSE, and MAPE .
• Utilize AWS cloud services to support model development and deployment.
• Build interactive dashboards using Streamlit, Plotly, or similar tools .
• Work closely with operations, engineering, and business stakeholders to translate complex data into actionable forecasts.
• Participate in Agile/Scrum ceremonies and contribute to technical leadership within the team.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or another quantitative field .
• 6–10+ years of professional Data Science, Machine Learning, or related experience.
• Advanced proficiency in Python , including libraries such as:
• pandas
• NumPy
• scikit-learn
• statsmodels
• Strong experience with time-series forecasting , including techniques such as:
• ARIMA
• SARIMAX
• Gradient Boosting
• Proven experience taking ML/forecasting models from development through production deployment .
• Strong SQL skills and experience working with large datasets.
• Experience developing automated data pipelines and integrating external APIs.
• Working knowledge of AWS , including services such as EC2, S3, Lambda, and SageMaker.
• Experience with Git/version control, model monitoring, and model maintenance .

Preferred Qualifications

• Experience with energy markets, utilities, load forecasting, solar forecasting, or wind generation forecasting .
• Experience incorporating weather data into forecasting models.
• Knowledge of MLOps and CI/CD pipelines .
• Experience with probabilistic forecasting and uncertainty quantification.
• Experience with Streamlit or Plotly .
• Familiarity with Jira and Confluence .
• Experience with Infrastructure-as-Code practices.

Ideal Candidate

The ideal candidate is a hands-on Data Scientist who is passionate about solving complex forecasting problems and has demonstrated experience building scalable, production-grade forecasting solutions . Strong communication skills and the ability to work with both technical and non-technical stakeholders are essential.

Keywords: Python, Data Science, Machine Learning, Time Series, Forecasting, ARIMA, SARIMAX, AWS, SageMaker, SQL, MLOps, Load Forecasting, Solar Forecasting, Wind Forecasting, Energy, Utilities, Weather Data, Streamlit, Plotly