Predictive Analytics & Forecasting Engine Development

The contract seeks the development of predictive analytics models to forecast day-ahead and real-time pricing, electricity demand, and congestion patterns for the ERCOT market, leveraging both historical and live data streams. The contractor will be responsible for designing, training, and validating machine learning models tailored to these specific forecasting needs, ensuring high accuracy and timely output to support grid operations. The models must be capable of continuous learning and adaptation as new data becomes available, with performance metrics aligned to industry standards for reliability and precision in energy market forecasting. The successful bidder will also deploy the finalized models onto a secure cloud infrastructure, ensuring scalability, low-latency access, and integration with existing operational systems used by ERCOT or its partners. While the solicitation originates from the City of Waterbury under NAICS code 541620 for scientific and technical consulting services, the work directly supports energy market operations in Texas, indicating a cross-jurisdictional application. The response deadline is June 24, 2026, and the contract is structured as a subcontract, suggesting it may be part of a broader initiative led by a prime contractor or government entity beyond the City of Waterbury.