Financial Analytics & Sales - Mitarbeiter (anonym) bei Bloomberg: Mitarbeiterbewertung

1,0
3. Mai 2017
Mitarbeiter (anonym)
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CEO-Befürwortung
Geschäftsprognose

Pros

Free food and access to influential people. Great for networking and being recruited to work for another company

Kontras

Horrible management in the analytics department. Absolutely NO diversity at all. They hire young attractive people fresh out of college. By the time the young folks leave they are simply brainwashed. When you start working here you will have to change the way you walk, talk, dress. Imagine yourself as dough- they will shape you and will bully you into becoming a differnt person or face firing.

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5,0
6. Mai 2026
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CEO-Befürwortung
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Pros

Great place to work if you are looking for work life balance

Kontras

The data department has very limited growth opportunities

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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