Power Systems Time-Series Analytics Intern

Intern - Power Systems Time-Series Analytics

Dominion Energy is committed to providing reliable, affordable, and increasingly clean energy that powers our customers every day. If you want to work for a purpose-driven company that values safety and collaboration, we’re looking for you. You won’t just find a job here; you’ll find your career. Review the position below.

We offer a hybrid 3-2 work schedule (three days in the office, two days of teleworking) to accommodate the need for flexibility.

We Strive to Drive Power Innovation Through Data

The nature of the grid is in flux. We on the Engineering Analytics & Modeling team see this challenge and aim to rise to the occasion. Our team mandate is simple: we aim to bridge the gap between real‑world system data and innovative capabilities that provide consumable business intelligence and help steer the future of how we monitor, plan, and manage the grid.

Our team is responsible for the capture, utilization, and application of time-series data, including synchrophasors, SCADA, point-on-wave measurements, load and generation data, and other supporting data. Our work is to steward this data and ensure its analysis and outputs influence our business and the industry as they adapt to meet the demands of a shifting energy landscape. We seek the curious, the self‑motivated, and those driven by the pursuit of change.

Job Summary:

We Seek Joint Expertise in Power Systems, Time-Series Analysis, and Data Analytics

Our team comprises a critical part of the Strategic Initiatives team within the Electric Transmission organization. We focus on addressing a broad spectrum of transformational and innovative projects by solving problems through real‑world measurements, data analytics, forecasting, statistical analysis, signal processing, and custom‑developed modeling and software capabilities.

The consistent thread across our work is the use of time-series measurement data to identify trends, understand system behavior, generate insights, and support better planning and operating decisions. A successful candidate will be able to:

• Navigate and interrogate an array of available power system and supporting data sources.
• Analyze time-series data across different time horizons and measurement resolutions.
• Identify trends, patterns, relationships, anomalies, and other insights within historical data.
• Support the development of analytical tools and capabilities aimed at observing, diagnosing, forecasting, and surfacing system behavior.
• Explore new applications of time-series analysis, statistical modeling, forecasting, signal analysis, or related methods within power systems.
• Apply statistical analysis, machine learning, and econometric methods to the development and evaluation of forecasting models.
• Explore longer‑horizon, scenario‑based, and probabilistic forecasting techniques to better characterize uncertainty and a range of potential future outcomes.
• Develop transparent, explainable, and presentable analyses or models that can be understood and used by technical and business stakeholders.
• Analyze and compare model or forecast outputs with actual system results, explain variances, and recommend potential improvements.
• Communicate findings through clear reports, visualizations, and presentations.

Candidates are not expected to have experience across every area of the team’s work. Experience or academic research in either of the following areas would be particularly valuable:

• Electric load, generation, renewable energy, or other forms of power system forecasting.
• Synchrophasor, phasor measurement unit, waveform, or point‑on‑wave data analysis, including the analysis of dynamic system behavior.

These backgrounds are appreciated but are not mandatory. Candidates with broader…