GE Vernova Advanced Battery Analytics Intern – Summer 2026
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About this role
Job Description Summary
Come and join our powerful, unified force with the energy to change the world. Our mission is BIG.
Our TRANSFORMATION is key – bringing the right businesses together to LEAD the ENERGY TRANSITION. Our TEAM is ready.
Addressing the climate crisis is an urgent global priority and we take our responsibility seriously. Building on over 130 years of experience tackling the world’s challenges, GE Vernova is uniquely positioned to help lead the energy transition by continuing to electrify the world while simultaneously working to decarbonize it. GE Vernova helps customers power economies and deliver electricity that is vital to health, safety, security, and improved quality of life.
Job Description
Battery energy storage systems (BESS) produce a significant amount of data through their operation. This presents a challenge for any BESS operator and manufacturer for how to manage and utilize that data. The battery analytics interns will be responsible for developing strategic and actionable viewpoints on how GEV stores, retrieves, and utilizes, and gains insights from BESS system data, as well as cell and module-based testing data.
The internship will be focused on three distinct projects, with flexibility to pursue related paths of research as the work develops:
- Project 1: Improved management of BESS assets through pattern data analysis
- Method: Look at available battery data, assess potential uses of battery data, advise on potential benefits of implementing new battery analytics tools
- Deliverable: Identified applications of battery data generated on site, which could be utilized by GEV for better asset performance in measurable ways, including the use of AI Agents and edge computing.
- Project 2: Development of enhanced data storage and retrieval mechanisms
- Method: Assess data types, and amounts, generated by BESS assets. Determine methods and value of improved compression in data, as well as benefit analysis as to what level of data validity is required for identified regular use cases.
- Project 3: Assessment of battery testing data and development of statistical models of battery performance for use in battery applications
- Method: analyze our internal testing data, determine margins on performance that suppliers give vs what we internally determine
- Deliverable: make recommendation on additional degradation, RTE, capacity, or other performance metrics that we could push the envelope on, above and beyond a 'back to back' agreement with the supplier, if GEV should so choose.
Primary Skills Developed:
- Battery Analytics
- Statistical analysis
- Data analytics
- Battery energy storage systems design and controls architecture
- Product development
- Product management
Internship Term Dates:
- May/June - August 2026
Expected Work Schedule:
- Day/1st -Shift (40 - hours weekly)
Qualifications:
Currently pursuing an Undergrad, Masters, Doctorate in:
- Data Science or Data Analytics
- Controls Engineering
- Electrical Engineering
- Industrial Engineering
- Chemical Engineering
- Materials Science & Engineering
- Mechanical
- Physics / Applied Physics
- Statistics
- Computer science or engineering
- Mathematics / Applied Mathematics
Desired Qualifications:
- Python, R, or other statistical software (preferred, but not required)
- Experience or aptitude for statistical modelling
- MS Office Suite, especially excel
- Strong analytical and critical thinking skills
- Knowledge or experience with energy storage systems
- Passion for renewable energy