Horrible company - Global Data bei Bloomberg: Mitarbeiterbewertung

1,0
3. März 2016
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Pros

There is free food, it is always a good name on your CV, they have nice and modern equipment and offices.

Kontras

Management is very poor, anyone can be a manager or team leader without any knowledge of the product as they only need to "get on well" with higher managers and "speak a lot". It does not matter how much you know or how well you do your job, if you do not sell yourself to managers and praise them, you will not get anywhere. A lot of people I know are being bullied at work, having work not being recognised, suffering from too much pressure and a huge work overload, always being told off for the smallest thing even if Management have no idea what their product is about. Too much control and too much micromanagement. Absolutely no work life as everyone is dead tired by the end of their shift (expect minimum 10 hours). Huge turnover, with people leaving every single month, nobody wants to stay. The atmosphere in the office is tense and unpleasant. Avoid at all costs.

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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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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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