Data Science Intern - RMCC (On-Site, San Jose)

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

Job summary

Bloom Energy Corporation is seeking a Data Science Intern for an on-site summer role in San Jose. You will analyze fuel cell data, validate degradation detection methods, and build automated workflows and dashboards for fleet monitoring.

The internship emphasizes Python, data analysis, and the development of scalable data pipelines, with collaboration across RMCC and engineering teams. Validating algorithms against real operations is key.

Qualifications

• Pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, Computer Engineering, or a related field.
• Must be graduating between spring 2027 and summer 2028

Responsibilities

• Analyze historical and real-time fuel cell operating data to identify degradation patterns and anomalous behavior.
• Validate existing Fuel Cell Degradation Detection algorithms using historical events and data.
• Evaluate detection accuracy including false positives and false negatives.
• Develop and optimize algorithms for earlier and more reliable degradation identification.
• Create automated data pipelines to monitor fleet data for degradation conditions.
• Develop dashboards and reporting tools to monitor algorithm performance.
• Collaborate with RMCC operators and engineers to validate results against operations.
• Document algorithms, validation methodologies, and performance results.

Skills

Python

Pandas/NumPy

SQL/NoSQL

REST APIs

Git

Data pipelines

Machine learning libraries

Dashboards

Automation

Education

Bachelor's or Master's in CS/DS/SE/CE

Tools

Git

Job description

Bloom Energy Corporation is seeking a Data Science Intern for an on-site summer role in San Jose. You will analyze fuel cell data, validate degradation detection methods, and build automated workflows and dashboards for fleet monitoring.

The internship emphasizes Python, data analysis, and the development of scalable data pipelines, with collaboration across RMCC and engineering teams. Validating algorithms against real operations is key.