Great company to begin - Account Manager bei Bloomberg: Mitarbeiterbewertung

2,0
5. Apr. 2010
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CEO-Befürwortung
Geschäftsprognose

Pros

-You will learn the markets and market players (concepts, roles, etc) -Human capital of various backgrounds/education/experience -Benefits package is very, very good -Brand name will not hurt your resume -Open culture/transparency(literally glass walls) -Free food -Amenities are great -Provided training on many various realms of finance -During the recession, the worry of unemployment never crossed the mind

Kontras

-Though you learn the markets and market players, you yourself are not a market player -Considered by the street as, and I quote: "Used car salesman" -Compensation is comparable to a UPS truck driver, but inflated with "certificates" based on a proprietary model that no one understands (Ref: Glassdoor UPS Truck Driver) -Too much transparency -Culture of passing it off to the next guy -Lack of professionalism -Micromanaging down to your daily schedule

Mehr Bewertungen zu Bloomberg entdecken

5,0
11. Juni 2026
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CEO-Befürwortung
Geschäftsprognose

Pros

Great company, in this role you have the chance to learn about the financial markets, the terminal, and also you get client exposure.

Kontras

Not really cons, culture is great.

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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