Data Analyst Intern

At Bloom Energy, our vision for a world powered by clean, reliable, and affordable energy is more than just a dream—we’re making it a reality. 
  
For over two decades, we’ve been at the forefront of the global energy transition, pioneering solutions that empower critical industries to thrive in a rapidly digitizing, energy-intensive world. From revolutionizing power for AI-driven data centers to ensuring resilience for hospitals, electric grids, manufacturing facilities, and utilities, our solid oxide fuel cell (SOFC) and solid oxide electrolyzer (SOEC) technologies are redefining what’s possible by delivering energy abundance for all. With more than 30,000 fuel cell modules deployed worldwide, we are the trusted partner for Fortune 100 companies and innovators alike. Our cutting-edge solutions enable unparalleled “time-to-power” capabilities, reliability, and sustainability, ensuring our customers remain ahead in a world where soaring energy demand and intensifying energy scarcity are rapidly becoming the new norm. 
  
At Bloom, we thrive on collaboration, bold thinking, and relentless innovation. We believe that, together, we can create a brighter, more sustainable future while tackling the most pressing challenges of the 21st century. 

Department Overview  

The Program Management team is responsible for the global program of fuel cell projects and plays a critical role in ensuring that strategic initiatives and complex projects are executed efficiently across Bloom’s organization.  

Position Responsibilities 

• Collect, clean, and analyze structured and unstructured data from various sources.  

• Build dashboards and reports using tools like Excel, Tableau, Power BI, or similar.  

• Assist in identifying trends, patterns, and anomalies in data sets.  

• Collaborate with cross-functional teams to understand data needs and deliver actionable insights.  

• Support the implementation of AI models for predictive analytics, classification, and automation.  

• Work with data scientists and engineers to integrate machine learning algorithms into business workflows.  

• Document methodologies, findings, and AI model performance in a clear and concise manner.  

• Contribute to ad hoc analysis and reporting requests. 

Minimum Qualifications 

• Currently a student earning a Bachelor’s in Data Science, Statistics, Mathematics, Computer Science, or a related field required.  

• Must be graduating between May 2026 and August 2027 

• Strong analytical and problem-solving skills.  

• Proficiency in Excel and at least one programming language (e.g., Python, R, SQL).  

• Familiarity with data visualization tools (e.g., Tableau, Power BI).  

• Excellent communication and collaboration skills.  

• Attention to detail and a passion for working with data and AI. 

Desired Qualifications 

• Experience with statistical analysis or machine learning concepts.  

• Prior internship or project experience involving data analysis or AI implementation.  

• Knowledge of cloud platforms (e.g., AWS, Azure). 

Visa Sponsorship   
Bloom Energy is unable to provide VISA sponsorship to interns or new grad hires on an F-1, J-1 or other visa for this position, regardless of CPT or OPT status. 

EOE Statement 
Bloom Energy is an equal opportunity employer and makes employment decisions on the basis of merit. We are committed to compliance with all applicable laws providing equal employment opportunities. All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, national origin, protected veteran status, or on the basis of disability. Bloom Energy makes reasonable accommodation, consistent with applicable laws, for the known physical or mental limitations of an otherwise qualified applicant or employee with a disability, who can perform the essential job functions, unless undue hardship would result. 

Salary Statement with pay range 
Bloom Energy is committed to fair and equitable compensation practices. The total compensation for this position is based on various factors including, but not limited to, relevant skills and experience.