Job Description

A retail energy provider (REP) in Houston is seeking a Load Forecasting Modeler to support its large and complex Commercial and Industrial (C&I) customers in the Northeast power markets. This position is responsible for developing and updating short- and long-term forecasting models using Python, SQL, and Machine Learning, as well as providing variance analysis and reporting of retail electricity components.

Responsibilities include:

• Data Management/Analysis: Utilize load, weather data, and economic data to incorporate into load forecasting models.
• Model Development: Build and maintain forecasting models (regression, neural networks, machine learning) to predict demand across different timeframes (short-term, long-term) and trends.
• Weather Integration: Incorporate weather forecasts (temperature, humidity, cloud cover) to adjust for weather-driven load changes.
• Forecast Generation: Produce forecasts for various horizons (e.g., next hour, day-ahead, seasonal peaks) for different customer segments.
• Market Support: Provide forecasts to retail power traders for strategic supply and hedging decisions.
• Reporting & Collaboration: Communicate forecasts, analysis, and potential risks to management, trading desks, and operations.

Essential Requirements:

• Bachelor’s degree in engineering, mathematics, or a related quantitative field.
• ~2-4 years of professional experience developing and maintaining mathematical models, preferably in electricity/power load forecasting or in data analytics supporting a Retail Energy Provider, Independent Power Producer (IPP), or a utility.
• Strong quantitative modeling (regression modeling, including neural-net, simple regression, and hybrid modeling) and statistical analysis (MAD, MAPE, etc.) skills.
• Advanced programming skills (Python, R, SAS, VBA, and Oracle SQL or SQL Server). Experience with LightGBM, CatBoost, and XGBoost is strongly preferred.
• Knowledge of and proficiency with data extraction, analysis, and reporting across complex system structures.
• Familiarity with deregulated power ISO markets, portfolio management and optimization, energy supply stack, load forecasting attributes, C&I customer profiling, etc., is preferred.

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