RUN!!! - Headline News Editor bei Bloomberg: Mitarbeiterbewertung

1,0
3. Mai 2010
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CEO-Befürwortung
Geschäftsprognose

Pros

Great pay, very plush office environment, offices are always in great locations, nice perks like an all you can eat snack bar, chauffered car to drop you to and from work if you're scheduled at certain hours, attracts very intelligent people.

Kontras

Very grueling environment, hires horrible trainers that don't train new employees properly, sink or swim mentality, prides itself on an 'open door' office environment but is actually the polar opposite, delivers candidates lots of fake promises in the interview process such as international opportunities, quick advancement, etc. senior management is trained to brainwash employees to operate on the fear of losing their jobs, management is free to practice verbal and emotional abuse on employees as a way to garner results, constant stress makes everyone extremely bad tempered so there is little positive interaction with colleagues, absolutely no room for creativity or ideas.

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5,0
22. Apr. 2026
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CEO-Befürwortung
Geschäftsprognose

Pros

Great culture, benefits, pay, and work-life balance

Kontras

The technical challenges can be a bit stagnant. You learn to deal with people rather than systems

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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