Operation Analyst
Position Summary & Responsibilities
Our Houston-based Retail team is focused on delivering exceptional service and a uniquely data-driven, tech-forward offering to commercial customers across the ERCOT and PJM markets.
At Gridmatic, we foster a workplace culture rooted in teamwork, continuous learning, and a strong commitment to diversity and inclusion. We move fast, solve problems with agility, and are both environmentally and data-driven. With a growth-oriented, academic mindset, we hold integrity and excellence as equal pillars of our success.
About this Role:
We are seeking a detail-oriented and highly motivated professional to join our Retail Operations team, focused on serving commercial electricity customers in ERCOT and PJM. This role is critical to ensuring the seamless execution of key operational functions including transactions, billing, and customer support.
The ideal candidate will have strong analytical and problem-solving skills, a proactive mindset, and the ability to thrive in a fast-paced, data-driven environment. You’ll work cross-functionally to drive accuracy, efficiency, and compliance across the retail energy and customer lifecycle, while delivering exceptional service to both customers and broker partners.
This is a high-impact role with broad exposure across the business, ideal for someone who enjoys working at the intersection of operations, data, and strategy.
Key Responsibilities:
1. Transactions
- Process enrollment, reject, disconnect, and reconnect transactions across ERCOT and
PJM - Ensure all commercial customers are enrolled accurately and on schedule
- Manage transaction exceptions and troubleshoot issues as they arise
2. Customer Service
- Perform call quality audits to ensure quality and consistency
- Support the customer support team with questions and maintain the customer care knowledge database
- Respond to customer inquiries and issues with clarity, professional
Key Role Competencies & Evaluation Highlights
Evaluating your ability to handle complex optimization problems, real-time energy markets, and data-driven decision making under uncertainty.
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