On-Site Summer Data Science Intern — Industrial Analytics

Bloom Energy; San Jose (CA); On-site; USD 50,000 - 69,000; Full time

Job summary

Bloom Energy is seeking a summer data science intern to join the Services Business Intelligence team on-site in the San Jose area. You will develop data science solutions for fleet optimization, predictive maintenance, and operational efficiency, delivering documented analysis and tested code.

The internship will involve preparing data, building ML models, and evaluating performance, with opportunities to deploy scalable workflows and collaborate with engineering, data science, and product teams.

Qualifications

• Pursuing Bachelor’s or Master’s degree in relevant field with expected graduation between spring 2027 and summer 2028.
• Solid foundation in Python, data science, and ML concepts.
• Experience with time-series data, forecasting, and model validation helpful.

Responsibilities

• Prepare, explore, and validate operational and time-series data.
• Develop and evaluate machine learning models for industrial applications.
• Improve data and software workflows supporting model development and deployment.
• Write tested, reusable Python code and technical documentation.
• Present findings and recommendations to technical and business stakeholders.

Skills

Python

SQL

Data science libraries

Machine learning

Forecasting

Time-series analysis

Git

Cloud platforms

Communication

Collaboration

Education

Bachelor’s or Master’s degree in Data Science, CS, Statistics, Electrical Engineering, Applied Mathematics, Industrial Engineering, or related field

Tools

Git

Cloud platforms

Job description

Bloom Energy is seeking a summer data science intern to join the Services Business Intelligence team on-site in the San Jose area. You will develop data science solutions for fleet optimization, predictive maintenance, and operational efficiency, delivering documented analysis and tested code.

The internship will involve preparing data, building ML models, and evaluating performance, with opportunities to deploy scalable workflows and collaborate with engineering, data science, and product teams.