Avoid if possible - Mitarbeiter (anonym) bei Bloomberg: Mitarbeiterbewertung

1,0
18. Apr. 2021
Mitarbeiter (anonym)
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CEO-Befürwortung
Geschäftsprognose

Pros

Looks great on CV Lots of opportunities to learn Standard benefits package, no better or worse than competition Easy to sell as dominates sector, twice more terminals than Refinitiv installed

Kontras

Long hours, standard 8-6 flat structure, takes ages to progress career Promotion is based on how manageable you are, are you willing to confirm to the culture Brightest people are never promoted When this is your first job in life be ready to work very very hard, and put up with lots of unfairness You will be clocked in and out all the time Bullying and harassment is part of culture although employee guide condemns it If you are on visa be ready to be exploited as the company knows you have no choice but to be compliant Work is mechanical as there are processes You have to log every move, call, meeting into crm You will fly a lot and stay in hotels a lot if you are in a sales role You will see zero smiles and happiness and soon you will be the same

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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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