Distribution Ops & Planning Engineer III in Knoxville, Tennessee at EPRI
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Job Description
Requisition ID: REQ-4064
Position Type: Full time
About Us: About Us
EPRI provides thought leadership, industry expertise, and collaborative value to help the electricity sector identify issues, technology gaps, and broader needs that can be addressed through effective research and development programs for the benefit of society.
If you need help during the application process, please contact us at applyhelp@epri.com.Job Title:Distribution Ops & Planning Engineer IIILocation:Knoxville, TNJob Summary and Description:
Utilities around the world are transforming their distribution systems to support electrification, distributed energy resources (DER), resilience, decarbonization, and growing operational complexity. As planning and operations become increasingly data-driven, utilities need advanced analytics, high-fidelity modeling, artificial intelligence, and trusted data to maintain a reliable, resilient, and efficient grid.
The EPRI Distribution Operations and Planning team leads collaborative research that advances the state of the art in distribution system planning and operations. Through the development of innovative methodologies, simulation tools, analytics, and field-validated solutions, the team addresses challenges spanning grid modernization, DER integration, protection, resilience, operations, and emerging technologies.
This position conducts research in advanced power system modeling, simulation, AI, machine learning, and measurement-based analytics. The successful candidate will develop and apply advanced analytical methods that combine power system models with data-driven approaches, leveraging utility data to improve planning, operations, and protection while translating cutting-edge research into practical solutions for the electric utility industry.
Key Responsibilities:
Makes significant contributions to advanced modeling, simulation, and analytics projects
Conducts independent research activities with guidance and contributes to development of new tools, methodologies, and research approaches to address industry challenges
Evaluate emerging technologies and applications through analytical and field-based studies
Contribute to technical publications, conference papers, webinars, and industry presentations
Support proposal development and strategic research planning activities
Engage with utility members to identify challenges, transfer research outcomes, and support technology adoption
Contribute to the development and evaluation of AI-enabled tools and analytics applications for utility planning and operations
Develop and apply repeatable processes for measurement data cleaning, quality assessment, and integration
Conduct model verification and validation activities using utility measurement data
Assess the applicability, limitations, and performance of emerging AI technologies within utility environments
Ideal candidate:
Strong knowledge of power system fundamentals, specifically distribution systems
Demonstrated experience developing software tools and analytical applications using Python, C#, Delphi, Java, or similar languages
Experience with distribution system model development, validation, and verification
Experience cleaning and utilizing utility measurement data from AMI, SCADA, and other field sources
Proven ability to conduct power systems analytical studies, with an emphasis on distribution modeling and simulation
Demonstrated experience with one or more industry modeling and simulation tools such as OpenDSS, CYME, Synergi, Milsoft, PowerFactory, EMTP, PSCAD
Experience applying AI, machine learning, or advanced analytics techniques to power system applications
Familiarity with modern AI and data science frameworks such as TensorFlow, PyTorch, Scikit-Learn, LLM-based systems, agentic workflows, or related technologies is desirable
Experience modeling high penetrations of DER, inverter-based resources, electrification technologies, and flexible loads
Preferred Education:
Bachelor’s degree in a technical field or equivalent experience
Preferred MS or PhD in Electrical Engineering with Power System emphasis
Minimum 2-3 years of engineering, utility, consulting, research, or equivalent experience preferred.