Job Description
Company Description
We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (18000+ experts across 40 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!
Role Overview
Nagarro is seeking an experienced ERCOT Market Subject Matter Expert to support a focused Proof of Concept for congestion driver attribution across the ERCOT nodal network.
The engagement aims to develop a Graph Neural Network-based solution that combines physical power-system fundamentals, market participant behaviour, and ERCOT transmission-network topology to identify and explain the key drivers of congestion.
The ERCOT SME will work closely with Graph ML engineers, data engineers, power-market analysts, and project leadership to ensure that the analytical models are grounded in ERCOT market principles and produce interpretable, actionable outputs.
Objectives of the Role
The ERCOT Market SME will be responsible for:
- Providing domain expertise on ERCOT market operations, congestion mechanisms, and nodal pricing.
- Guiding the interpretation of transmission constraints, shift factors, shadow prices, binding intervals, and congestion propagation.
- Supporting the definition and validation of congestion-driver categories.
- Translating ERCOT market behaviour into functional and analytical requirements for the data science and Graph ML teams.
- Ensuring that model outputs are understandable and relevant to power-market analysts and trading stakeholders.
- Validating congestion attributions against independently verifiable historical ERCOT market events.
- Supporting the assessment of the model’s readiness for future nodal price-forecasting use cases.
Job Description
ERCOT Market and Congestion Expertise
- Explain ERCOT nodal market design, settlement-point pricing, transmission congestion, and Locational Marginal Pricing components.
- Analyse 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 behaviour.
- Interpret participant-level and aggregated bid-and-offer disclosures within the context of congestion and shadow-price formation.
Model and Data Support
- 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 the separation and interpretation of physical and behavioural contributors to observed congestion.
- Help establish business rules, assumptions, thresholds, and domain constraints for model development.
Validation and Interpretation
- 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 that model outputs can be interpreted by market analysts without requiring advanced machine-learning knowledge.
Stakeholder Collaboration
- 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, modelling assumptions, or ERCOT-specific interpretation.
Qualifications
Demonstrated professional experience working with the ERCOT wholesale electricity market, with a strong understanding of congestion modelling 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 analysing historical congestion events and identifying the underlying physical, transmission, or market-behaviour drivers.
Experience in one or more areas such as power-market trading, congestion analytics, forecasting, market simulation, production-cost modelling, power-flow analysis, or transmission-network modelling.
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 would be advantageous.
Additional Information
Disclaimer: Nagarro is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will be afforded equal employment opportunities without discrimination based on race, creed, color, national origin, sex, age, disability, or marital status.
