Jobs → Customer Support → Business Analysis - ERCOT Market Subject Matter Expert

About the Role We are seeking an ERCOT Market Subject Matter Expert to support a focused Proof of Concept for congestion driver attribution across the ERCOT nodal network. This role involves developing a Graph Neural Network-based solution that combines physical power-system fundamentals, market participant behavior, and ERCOT transmission-network topology to identify and explain the key drivers of congestion. Key Responsibilities • Provide domain expertise on ERCOT market operations, congestion mechanisms, and nodal pricing. • Guide the interpretation of transmission constraints, shift factors, shadow prices, binding intervals, and congestion propagation. • Support the definition and validation of congestion-driver categories. • Translate ERCOT market behavior into functional and analytical requirements for the data science and Graph ML teams. • Ensure that model outputs are understandable and relevant to power-market analysts and trading stakeholders. • Validate congestion attributions against independently verifiable historical ERCOT market events. • Support the assessment of the model’s readiness for future nodal price-forecasting use cases. Requirements • Explain ERCOT nodal market design, settlement-point pricing, transmission congestion, and Locational Marginal Pricing components. • Analyze binding transmission constraints, contingency conditions, shift-factor exposures, shadow prices, and historical binding hours. • Support the identification of congestion caused by generation outages, renewable oversupply, load concentration, transmission outages, contingencies, and market participant behavior. • Interpret participant-level and aggregated bid-and-offer disclosures within the context of congestion and shadow-price formation. • Work with the Graph ML team to define appropriate node, edge, transmission, market, and temporal attributes for the ERCOT network graph. • Review the use of ERCOT transmission models, shift-factor matrices, contingency files, line ratings, outage feeds, market disclosures, and historical congestion information. • Define a practical taxonomy for congestion-driver attribution.