Great Company, low pay - Project Coordinator Bloomberg Employee Review

3.0
May 31, 2011
Recommend
CEO approval
Business Outlook

Pros

The benefits package is great without a doubt. That is probably the best thing about the company. Also the free snacks in the pantry. We have discounts and perks and certain stores, gyms, etc.

Cons

The pay is low. If you don't come to the company already demanding a high salary then it will take forever to get salary increases. Also salary increases only happen once a year! Even if you move into a new position, you don't get your new salary, so you can spend months working in a higher paying role, but the new salary doesn't kick in until the 1 year period. Also the long hours. The norm is to work 9/10 hour days depending on what dept you are in, but if you are overloaded with work (which is pretty often) you're looking at 10 /11 hour days! Most of the time upper management doesn't recognize the extra time that you're putting in anyway.

Explore other reviews about Bloomberg

5.0
Jun 11, 2026
Recommend
CEO approval
Business Outlook

Pros

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

Cons

Not really cons, culture is great.

4.0
Jun 28, 2026
Recommend
CEO approval
Business Outlook

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.

Cons

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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