Honest review - Analytics & Sales bei Bloomberg: Mitarbeiterbewertung

1,0
30. Okt. 2025
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CEO-Befürwortung
Geschäftsprognose

Pros

- you work a strict 8 to 6, dont bring home any work - better than average starting pay, >6k, within 2 years can achieve 8-10k, worth doing it for the money - free breakfast, lots of pantry snacks - can request for herman miller chair - 20 days leave

Kontras

- your work schedule is decided for you. Lunch time is decided by manager, capped at 1 hour. Cannot use toilet for too long without affecting KPI - managers like to force people to come up with projects on top of BAU work, or else you have "poor performance" - main bulk of job is being on the helpdesk, just answering questions. Occasional sales element when you get to tag along the actual sales team - not much exit opportunities, knowledge is very bloomberg centric (can go to competitor company like S&P, LSEG)

Mehr Bewertungen zu Bloomberg entdecken

5,0
8. Juli 2026
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CEO-Befürwortung
Geschäftsprognose

Pros

good pay, great team, lots of experience gained

Kontras

mundane tasks sometimes, can be competitive

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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