Lead Energy Forecasting & AI Analytics (Remote)

GE Vernova; Cambridge (MA); On-site; USD 112,000 - 186,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

Health Coach

Employee Assistance Program

401(k) with company matching

Tuition assistance

Adoption assistance

Paid parental leave

Disability benefits

Life insurance

12 paid holidays

Permissive time off

Job summary

GE Vernova is modernizing its forecasting capabilities to improve the accuracy, efficiency, and strategic value of its power system outlooks. The Lead Analyst, Energy Forecasting & Advanced Analytics will help build GE Vernova’s next‑generation forecasting platform by contributing to model development, data engineering, automation, advanced analytics, and operational execution.

This hands-on role translates strategy into scalable, production‑ready forecasting capabilities while supporting the

Qualifications

• Bachelor's degree in engineering, data science, economics, or a related field is required.
• 3–5 years of energy analytics, forecasting, power markets, or related technical field experience.
• Proficiency with Python, R, Julia or similar and experience with large datasets.

Responsibilities

• Build and maintain components of capacity expansion models, production cost and dispatch models, and scenario analysis frameworks.
• Develop and maintain data pipelines for internal and external datasets; clean and transform large datasets for modeling.
• Create analytical tools and automation to modernize forecasting workflows and improve scalability.

Skills

Python

R

Julia

Large datasets

AI in analytics

Education

Bachelor's degree in engineering, data science, economics, or related field

Tools

SQL

Cloud platforms

APIs

Power BI

Python

Job description

GE Vernova is modernizing its forecasting capabilities to improve the accuracy, efficiency, and strategic value of its power system outlooks. The Lead Analyst, Energy Forecasting & Advanced Analytics will help build GE Vernova’s next‑generation forecasting platform by contributing to model development, data engineering, automation, advanced analytics, and operational execution.

This hands-on role translates strategy into scalable, production‑ready forecasting capabilities while supporting the