Solar and Energy Storage Remote Operator and Data Analyst

Ameresco, Inc. (NYSE:AMRC) is a leading energy solutions provider dedicated to helping customers reduce costs, enhance resilience, and decarbonize to net zero in the global energy transition. We are a trusted, full-service partner to public sector and government entities, K-12 schools, higher education, utilities, and healthcare customers across the U.S., Canada, the U.K., and Europe.

At Ameresco, we show the way by developing, constructing and operating tailored smart energy efficiency solutions, distributed energy resources, and infrastructure upgrades that drive cost savings, resilience, decarbonization, and innovation. Our comprehensive portfolio is built to address the challenges of today and adapt the future, ensuring long-term sustainability and success for our customers.

Ameresco is seeking a highly analytical and detail-oriented Solar and Energy Storage Remote Operator & Data Analyst to support the monitoring, analysis, and optimization of Solar and Energy storage systems performance. This position will be on on-site at the Westborough, MA location. Candidates must have an electrical engineering degree or electrical license with 2 + of solar operations and maintenance experience. This is an overnight role, with the hours being 8:00 PM-5:00 AM, either Tuesday-Saturday or Sunday-Thursday.

Responsibilities:

• Monitor real-time data from Solar and Energy Storage sites to identify anomalies, trends, and performance deviations.

• Ability to technically troubleshoot commercial solar PV and BESS systems remotely

• Analyze system performance metrics to ensure optimal efficiency, reliability, and compliance with industry standards.

• Ability to handle complex and critical issues in a timely manner.

• Collaborate with technical teams to diagnose system issues and propose corrective actions.

• The ability to remotely diagnose, troubleshoot, and reset equipment.

• Utilize data visualization tools and software to present insights effectively to management and engineering teams.

• Support predictive analytics models for performance forecasting and preventative maintenance planning.

• Maintain and improve data integrity, ensuring accurate and timely documentation of all analytical findings.

• Investigate historical trends to optimize system configurations and improve future deployments.

Minimum Qualifications:

• Minimum of 2+ years of experience with machine learning applications for predictive maintenance in PV and BESS systems.

• Electrical Engineering Degree

Additional Qualifications:

• Prior experience working or interacting with commercial PV and BESS projects

• Comfortable working independently, ensuring seamless handover to the next working shift.

• Preferred Qualifications and Experience:

• Electrical engineering degree or electrical license with two years + of solar operations and maintenance experience.

• NERC certified as System Operator or is working to gain certification.

• Strong proficiency in data analysis tools such as Python, SQL, Excel, and visualization platforms (Power BI, Tableau).

• Familiarity with SCADA systems, monitoring platforms, and renewable energy asset management software.

• Excellent problem-solving skills with a keen eye for identifying inefficiencies and optimization opportunities.

• Ability to interpret large datasets and translate findings into actionable insights for technical teams.

• Strong written and verbal communication skills to articulate complex technical data in a concise manner.

• Knowledge of grid-scale energy storage operations, market dynamics, and regulatory frameworks.

• Certifications in energy analytics, data science, or renewable energy technologies.

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Ameresco challenges the brightest, most talented, and creative individuals in the industry by providing an environment that fosters initiative and achievement. We are proud of our comprehensive and competitive employee benefits, including people-oriented insurance, investment, and incentive plans.

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Ameresco is an Equal Opportunity Employer.