Remote Senior Energy Forecasting & AI Analytics Lead

GE Vernova, Inc.

Greenville (SC)

On-site

USD 112,000 - 186,000

Full time

2 days ago
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Benefits offered by this job

Medical benefits
Dental benefits
Vision benefits
401(k) with company matching
Paid holidays

Job summary

GE Vernova is seeking a Lead Analyst in Energy Forecasting & Advanced Analytics to help build its next-generation forecasting platform. The role combines model development, data engineering, automation, and advanced analytics to translate strategy into scalable, production-ready forecasting capabilities.

You will develop capacity expansion and dispatch models, build data pipelines, and apply AI-enabled approaches to improve forecasting workflows.

Qualifications

  • Bachelor's degree in engineering, data science, economics or related field.
  • 3–5 years of energy analytics or related technical field.
  • Strong proficiency with Python, R, Julia or similar.
  • Experience with large datasets and analytical workflows.
  • Experience applying AI, analytics or quantitative methods in market analysis or forecasting.

Responsibilities

  • Build and maintain capacity expansion, production cost and dispatch models and scenario analyses.
  • Translate inputs into structured, testable model logic.
  • Develop and maintain data pipelines for internal and external datasets.
  • Clean, transform and validate large datasets for modeling use.
  • Develop analytical tools in Python, R or Julia and automate forecasting processes.
  • Collaborate with domain experts and prepare insights for stakeholders.

Skills

Python
R
Julia

Education

Bachelor's degree in engineering or related field

Tools

SQL
Cloud platforms
APIs
Power BI

Job description

GE Vernova is seeking a Lead Analyst in Energy Forecasting & Advanced Analytics to help build its next-generation forecasting platform. The role combines model development, data engineering, automation, and advanced analytics to translate strategy into scalable, production-ready forecasting capabilities.

You will develop capacity expansion and dispatch models, build data pipelines, and apply AI-enabled approaches to improve forecasting workflows.

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