Principal Data Scientist - Load & Renewable Forecasting in , United States

Principal Data Scientist - Load & Renewable ForecastingWe are seeking a Principal Data Scientist to lead the development and production deployment of advanced forecasting models for Load, Solar, and Wind . This role supports critical decision-making for energy management and system operations. This position will engage in end-to-end model development, including feature engineering, data integration, model optimization, and performance monitoring. The successful candidate will design production-ready forecasting solutions integrated with internal systems and cloud infrastructure.Key ResponsibilitiesLead 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.Develop data connectors for weather APIs and data warehouse systems.Design scalable pipelines for real-time and batch forecasting operations.Create interactive dashboards using tools like Streamlit

and present insights to stakeholders.Understand business priorities and take ownership of the complete model lifecycle.Collaborate with trading, operations, and engineering teams.Work effectively within Agile frameworks and participate in scrum ceremonies.Deliver high-quality forecasting solutions that meet operational deadlines and accuracy standards.Required QualificationsEducation: A Bachelor’s or Master’s degree in a quantitative field is required.Experience: This role requires 6-10 years of professional data science experience. This includes a proven track record of developing and deploying production forecasting models (e.g., ARIMA, SARIMAX, gradient boosting methods) and taking models from research through to production with versioning, monitoring, and maintenance.Technical Skills:Advanced proficiency in Python with extensive experience in data science libraries (pandas, numpy, scikit-learn, statsmodels).Experience consuming and integrating weather APIs and external data sources into forecasting pipelines.Working knowledge of AWS services (EC2, S3, Lambda, SageMaker) and Infrastructure-as-Code practices.Proficiency with SQL databases and experience with large-scale data queries and optimization.Experience building interactive dashboards using Streamlit, Plotly, or similar frameworks.Knowledge of feature engineering with weather variables, model evaluation metrics (MAE, RMSE, MAPE), and version control (Git). QualificationsExperience with MLOps and CI/CD pipelines.Knowledge of advanced feature engineering, uncertainty quantification, and probabilistic forecasting methods.Domain expertise in energy markets and renewable forecasting.Familiarity with Agile project management tools (Jira, Confluence).