No flat structure.... - Mitarbeiter (anonym) bei Bloomberg: Mitarbeiterbewertung

2,0
21. Feb. 2010
Mitarbeiter (anonym)
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CEO-Befürwortung
Geschäftsprognose

Pros

The office is beautyful and you probably won't find much better anywhere else. People are also great and it's an excellent place to make new friends and meet people from all around the world. It's a not a bad place to start your career but don't stay too long!

Kontras

Salary is not competitive at all which is very demotivating. Career prospects are poor and senior management have not been trained in leadership at all. Working hours are NOT flexible. You often feel like working in a factory and all that is important is statistics before quality. It doesn't feel like management cares about you at all which is bad for moral and team spirit. Lastly, Bloomberg is known for having a very flat structure which is not really true. Even people used to working in investment banks say that Bloomberg's management structure is more hierarchical than those in banks. Unless you know the right people in the US it is very difficult to get a say in anything.

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5,0
11. Juni 2026
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CEO-Befürwortung
Geschäftsprognose

Pros

Great company, in this role you have the chance to learn about the financial markets, the terminal, and also you get client exposure.

Kontras

Not really cons, culture is great.

4,0
28. Juni 2026
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CEO-Befürwortung
Geschäftsprognose

Pros

Opportunities to do lots of work with data and finance to apply knowledge in both programming and Subject-Matter Expertise (SME). Excellent Work-Life Balance (WLB) and extremely welcoming culture. You can reach out to anyone for help or just to talk, and they will get back to you (although management does require more scheduling in advance). Generous compensation (good wage) and benefits, including housing for interns. If you heard the rumors that the Bloomberg Princeton office has a great Bloomberg Pantry (read: company-provided breakfast and lunch), the rumors are true.

Kontras

Not the place for those looking for cutting-edge AI. The company is not as fast with AI as the company prioritizes reliability and accuracy above all, and much of AI is not at an acceptable threshold for management to be willing to take that risk with financial data (at least in 2026). You may get a project to automate menial processes, which is really cool, but that tends to involve actually doing the menial processes, which feels unproductive. Princeton office is good but New York is considered preferable. Coworkers are not very reachable outside of work hours. Compensation is low in Data compared to Software Engineers.

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