Power Systems Time-Series Analytics Intern (Hybrid)

Dominion Energy; Richmond (VA); Híbrido; USD 47.000 - 58.000; A tiempo parcial

Ventajas ofrecidas por este puesto de trabajo

Tuition reimbursement

401k with match

Paid holidays

Vacation

Descripción de la vacante

Dominion Energy in Richmond, VA seeks an Intern for Power Systems Time-Series Analytics to work with time-series data across load, generation, SCADA, and synchrophasor sources. You will develop analytical tools and forecasting methods for better system understanding and planning.

The role emphasizes statistical modeling, data science, and transparent communication with technical and business stakeholders. Hybrid schedule and internship terms apply.

Formación

• Graduate-level study in engineering, math, stats, CS, or data science.
• Electrical engineering with power systems focus is preferred but not required when time-series experience exists.
• Graduating Spring 2028 or later; GPA 3.5+.

Responsabilidades

• Navigate and interrogate power system data sources (load, generation, SCADA, synchrophasor).
• Analyze time-series data across time horizons and resolutions.
• Identify trends, patterns, and anomalies in historical data.
• Develop analytical tools for observing, diagnosing, forecasting, and surfacing system behavior.
• Explore forecasting, signal analysis, and probabilistic methods for power systems.
• Communicate findings via reports, visualizations, and presentations.

Conocimientos

Time-series

Python

Statistics

Analytical programming

Communication skills

Critical thinking

Ethics

Data science

Educación

Graduate degree candidate in engineering/math/statistics

Electrical engineering with power systems focus preferred

Herramientas

Python libraries (SciPy/NumPy)

Statistical analysis libraries

Machine learning libraries

Descripción del empleo

Dominion Energy in Richmond, VA seeks an Intern for Power Systems Time-Series Analytics to work with time-series data across load, generation, SCADA, and synchrophasor sources. You will develop analytical tools and forecasting methods for better system understanding and planning.

The role emphasizes statistical modeling, data science, and transparent communication with technical and business stakeholders. Hybrid schedule and internship terms apply.