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

Principal Data Scientist

Similar Data Science Jobs

Data Science Director - Infrastructure Data Center Analytics

Data Scientist--JIATF

Manager, Data Science and Analytics

Director, Data Science and Analytics

Variant Assessment Scientist I– Cardiology (REMOTE, USA)

Research Engineer / Research Scientist, RL Frontiers