Remote Data Science Intern: Fleet Analytics & Automation

101 Bloom Energy; Concord (NH); On-site; USD 50,000 - 69,000; Part time

Job summary

Bloom Energy offers an internship in the Remote Monitoring Control Center (RMCC) focused on analyzing fuel cell data to identify degradation and improve detection accuracy. Interns will validate degradation algorithms, develop automated pipelines, and create dashboards to monitor performance.

The role emphasizes Python, Pandas/NumPy data analysis, and collaboration with RMCC engineers to ensure results align with real operating conditions. Graduation window: 2027–2028.

Qualifications

• Currently 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 abnormal operating behavior.
• Validate existing Fuel Cell Degradation Detection algorithms using known historical events and operational data.
• Evaluate detection accuracy, including false positives, false negatives, precision, and recall.
• Develop and optimize algorithms for earlier and more reliable identification of fuel cell degradation.
• Use Python and statistical analysis to evaluate operating trends, thresholds, correlations, and anomalies.
• Develop automated data pipelines and tools to continuously monitor fleet data for potential degradation conditions.
• Automate workflows from detection → validation → notification → action tracking → resolution.
• Develop dashboards and reporting tools to monitor detected conditions and algorithm performance.
• Collaborate with RMCC operators and engineers to validate algorithm results against actual operating conditions.

Skills

Python

Algorithms

Data analysis

SQL/NoSQL

Education

Bachelor's or Master's degree

Tools

Pandas

NumPy

Git

REST APIs

Job description

Bloom Energy offers an internship in the Remote Monitoring Control Center (RMCC) focused on analyzing fuel cell data to identify degradation and improve detection accuracy. Interns will validate degradation algorithms, develop automated pipelines, and create dashboards to monitor performance.

The role emphasizes Python, Pandas/NumPy data analysis, and collaboration with RMCC engineers to ensure results align with real operating conditions. Graduation window: 2027–2028.