RMCC Data Science Intern
About The Position
Bloom Energy is hiring a Remote Monitoring Control Center (RMCC) Data Science Intern for a summer internship beginning in May or June. The position is fully on-site at the listed office location. RMCC monitors, optimizes, and supports field services for Bloom Energy’s fleet of more than 30,000 fuel cells deployed worldwide. The intern’s anticipated primary project is to analyze fuel cell operational data, validate existing degradation-detection logic, improve detection accuracy, and automate workflows from detection and validation through notification, tracking, and resolution. The project may change before the internship, and interns may also work on additional projects. The role involves analyzing historical and real-time fleet data, evaluating and improving detection algorithms, creating data pipelines and monitoring tools, developing dashboards and reports, and working with RMCC operators and engineers to compare algorithm results with actual operating conditions. The intern will document algorithms, validation methods, automated workflows, and performance results. The hourly pay range is $36–$50; the salary range is separately listed as $36.00–$39.00.
Requirements
- 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.
Nice To Haves
- Proficiency in Python.
- Strong understanding of algorithms, data structures, and software development.
- Experience with data analysis using Pandas, NumPy, or similar tools.
- Strong analytical and problem-solving skills.
- Ability to work with large datasets and translate operational requirements into software solutions.
- Experience with SQL/NoSQL databases, REST APIs, Git, and data pipelines.
- Knowledge of statistical analysis, anomaly detection, classification, or time-series analysis.
- Familiarity with machine-learning libraries.
- Experience developing automation, monitoring applications, dashboards, or engineering tools.
- Interest in energy systems, predictive analytics, reliability engineering, or AI/ML.
- Ability to evaluate algorithm performance using measurable metrics and test datasets.
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 through validation, notification, action tracking, and 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.
- Document algorithms, validation methodologies, automated workflows, and performance results.
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What This Job Offers
Career Level
Intern
