Associate Director - ERCOT Market Subject Matter Expert (Part-Time/ Contract)

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About the role

Nagarro is seeking an experienced ERCOT Market Subject Matter Expert to support a Proof of Concept for congestion driver attribution across the ERCOT nodal network. This engagement aims to develop a Graph Neural Network-based solution combining physical power-system fundamentals, market participant behavior, and ERCOT transmission-network topology to identify and explain key congestion drivers. The ERCOT SME will collaborate closely with Graph ML engineers, data engineers, power-market analysts, and project leadership to ensure analytical models are grounded in ERCOT market principles and produce interpretable, actionable outputs.

Responsibilities

• Provide domain expertise on ERCOT market operations, congestion mechanisms, and nodal pricing.
• Guide interpretation of transmission constraints, shift factors, shadow prices, binding intervals, and congestion propagation.
• Support definition and validation of congestion-driver categories.
• Translate ERCOT market behavior into functional and analytical requirements for data science and Graph ML teams.
• Ensure model outputs are understandable and relevant to power-market analysts and trading stakeholders.
• Validate congestion attributions against independently verifiable historical ERCOT market events.
• Support assessment of the model’s readiness for future nodal price-forecasting use cases.
• 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 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.
• Support separation and interpretation of physical and behavioral contributors to observed congestion.
• Help establish business rules, assumptions, thresholds, and domain constraints for model development.
• Validate model-generated congestion attributions against known historical events, including documented unit outages, transmission outages, curtailment events, and contingency-driven constraints.
• Review propagation paths and assess whether identified node and interface impacts are electrically and commercially plausible.
• Evaluate the accuracy and usefulness of model explanations, confidence scores, and shadow-price attribution.
• Participate in back-testing reviews and assist in comparing model performance against baseline approaches.
• Ensure model outputs can be interpreted by market analysts without requiring advanced machine-learning knowledge.
• Collaborate with the client’s trading, analytics, and power-market teams during architecture reviews and validation checkpoints.
• Participate in regular working sessions with Nagarro’s Graph ML engineers, data engineers, and project leadership.
• Present findings, assumptions, limitations, and recommendations in clear business and market terminology.
• Support risk identification and timely escalation of issues related to market data, modeling assumptions, or ERCOT-specific interpretation.

Requirements

• Demonstrated professional experience working with the ERCOT wholesale electricity market, with a strong understanding of congestion modeling and nodal market operations.
• Practical knowledge of:
  • Locational Marginal Pricing and congestion components
  • Shift factors and transmission-interface exposure
  • Binding constraints, contingencies, and constraint shadow prices
  • Day-Ahead and Real-Time Market operations
  • Generation, load, and transmission outages
  • ERCOT bid-and-offer disclosures
  • Congestion Revenue Rights and related market information
• Experience analyzing historical congestion events and identifying underlying physical, transmission, or market-behavior drivers.
• Experience in one or more areas such as power-market trading, congestion analytics, forecasting, market simulation, production-cost modeling, power-flow analysis, or transmission-network modeling.
• Familiarity with ERCOT datasets, including network-model files, outage reports, market disclosures, constraint reports, and other publicly available market information.
• Ability to translate complex power-market concepts into clear requirements and validation criteria for data engineering, analytics, and machine-learning teams.
• Experience collaborating with data scientists, machine-learning engineers, trading teams, or advanced analytics stakeholders.
• Strong analytical, communication, and stakeholder-management skills.
• Exposure to nodal price forecasting, explainable AI, graph-based analytics, or AI-led power-market applications (advantageous).