Intern - Power Systems Time-Series Analytics
About The Position
Dominion Energy’s Engineering Analytics & Modeling team works to connect real-world power-system data with analytical capabilities that provide business intelligence and inform how the grid is monitored, planned, and managed. The team captures, uses, and applies time-series data, including synchrophasors, SCADA, point-on-wave measurements, load and generation data, and supporting data. As an intern on the Strategic Initiatives team within Electric Transmission, you will support transformational and innovative projects using real-world measurements, data analytics, forecasting, statistical analysis, signal processing, and custom modeling and software. The work focuses on using time-series measurement data to identify trends and system behavior, generate insights, and support planning and operating decisions. The position offers a hybrid schedule of three days in the office and two days of teleworking. Candidates are not expected to have experience in every area. Experience or academic research in electric load, generation, renewable energy, or other power-system forecasting, or in synchrophasor, phasor measurement unit, waveform, or point-on-wave data analysis, is particularly valuable but not mandatory. Candidates with broader experience in time-series analysis, statistical modeling, signal processing, measurement analysis, or data-intensive engineering applications are encouraged to apply.
Requirements
- Strong engineering or quantitative background; a power-systems background is preferred.
- Strong understanding of statistical approaches for time-series data and the mathematical intuition to assess when and why methods are appropriate.
- Strong analytical programming skills, preferably in Python, including experience with scientific computing, statistical analysis, and machine-learning libraries.
- Ability to develop transparent, explainable, and reproducible analyses.
- Ability to think abstractly, investigate unfamiliar problems, persevere through challenges, and explore alternative methods while maintaining analytical rigor.
- Ability to work independently while remaining aligned with the team's mission.
- Ability to communicate complex analytical results clearly to technical and nontechnical audiences.
- Excellent professional ethics and responsible handling of operational and business data.
- Must be working toward a graduate-level degree in engineering, mathematics, statistics, computer science, data science, or a related technical discipline.
- Must be graduating in Spring 2028 or later.
- Must have a GPA of 3.5 or above.
Nice To Haves
- Electrical engineering focus on power systems.
- Experience with power-system measurements and operational data such as load, generation, SCADA, synchrophasor, or waveform data.
- Experience with statistical modeling, machine learning, forecasting, signal processing, econometrics, or probabilistic methods.
- Experience or academic research in electric load, generation, renewable energy, or other power-system forecasting.
- Experience or academic research analyzing synchrophasor, phasor measurement unit, waveform, or point-on-wave data, including dynamic system behavior.
- Broader experience in time-series analysis, statistical modeling, signal processing, measurement analysis, or data-intensive engineering applications.
Responsibilities
- Navigate and interrogate 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 in historical data.
- Support the development of analytical tools and capabilities to observe, diagnose, forecast, and surface system behavior.
- Explore applications of time-series analysis, statistical modeling, forecasting, signal analysis, and related methods within power systems.
- Apply statistical analysis, machine learning, and econometric methods to develop and evaluate forecasting models.
- Explore longer-horizon, scenario-based, and probabilistic forecasting techniques to characterize uncertainty and possible future outcomes.
- Develop transparent, explainable, and presentable analyses or models for technical and business stakeholders.
- Compare model or forecast outputs with actual system results, explain variances, and recommend potential improvements.
- Communicate findings through reports, visualizations, and presentations.
Benefits
- Health, dental, and vision benefits with coverage for families and domestic partners
- Vacation
- Retirement plans, including 401(k) contributions and matching
- Paid holidays
- Tuition reimbursement
- Bonus eligibility
- Sick leave
- Disability insurance
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What This Job Offers
Job Type
Full-time
Career Level
Intern
