Distribution Grid Modeling and Analytics - Engineer Staff III

EPRI•Knoxville, TN

About The Position

The EPRI Distribution Operations and Planning team conducts collaborative research to advance distribution system planning and operations. Its work addresses grid modernization, distributed energy resource integration, protection, resilience, operations, and emerging technologies through innovative methodologies, simulation tools, analytics, and field-validated solutions. This position conducts research in advanced power system modeling, simulation, artificial intelligence, machine learning, and measurement-based analytics. The successful candidate develops and applies analytical methods that combine power system models with data-driven approaches, using utility data to improve planning, operations, and protection. The role also translates research into practical solutions for the electric utility industry. The position is based out of EPRI’s Knoxville, Tennessee office, with remote work considered for the right candidate. The role is eligible for EPRI’s annual incentive program and standard employee benefits. The stated annual salary range is $92,000 to $101,000 USD; actual pay may vary based on factors including education, experience, skills, abilities, internal equity, market data, and geographic location.

Requirements

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 using 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, or PowerFactory.
Experience applying AI, machine learning, or advanced analytics techniques to power system applications.
Bachelor’s degree in a technical field or equivalent experience is preferred.
A minimum of 2–3 years of engineering, utility, consulting, research, or equivalent experience is preferred.

Nice To Haves

A preferred MS or PhD in Electrical Engineering with a power systems emphasis.
Familiarity with modern AI and data science frameworks such as TensorFlow, PyTorch, Scikit-Learn, LLM-based systems, agentic workflows, or related technologies.
Experience modeling high penetrations of DER, inverter-based resources, electrification technologies, and flexible loads.

Responsibilities

Make significant contributions to advanced modeling, simulation, and analytics projects.
Conduct independent research activities with guidance and contribute to developing tools, methodologies, and research approaches for 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 using utility measurement data.
Assess the applicability, limitations, and performance of emerging AI technologies within utility environments.