RMCC Data Science Intern
About The Position
The RMCC Data Science Intern will work on a summer internship project supporting Bloom Energy’s Remote Monitoring Control Center, which monitors, optimizes, and supports field services for its worldwide fleet of more than 30,000 fuel cells. The anticipated primary project is to analyze fuel cell operational data, validate and improve degradation-detection logic, and automate the process from detection and validation through notification, tracking, and resolution. The project may change before the internship, and interns may work on additional projects. The position is fully on-site and is expected to start in May or June. The internship is intended for students pursuing a bachelor’s or master’s degree in a relevant computing or data-related field who will graduate between spring 2027 and summer 2028. The stated pay range is $36–$50 per hour; a separate salary range is 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
