Great Employee Benefits, Beautiful Building, A Lot of Bureaucracy - Mitarbeiter (anonym) bei Bloomberg: Mitarbeiterbewertung

3,0
5. Mai 2015
Mitarbeiter (anonym)
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Pros

They have the best healthcare and employee benefits, with access to some of the best resources to advance your career. The HQ building is beautiful in a prime location with nice fish tanks and tons of food, oftentimes hosting cutting edge events. The perks of being an employee are truly top notch (e.g. museums, discounts).

Kontras

Can be Big Brother-ish. You have to use the ancient-looking Terminal to do conduct all business activity (somewhat of a learning curve). Lots of bureaucracy and useless middle management to "track projects and progress." Insignificant or non-existent promotions/salary increases. The fear of Tom Secunda is laughable.

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5,0
8. Juli 2026
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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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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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