Great place to learn and grow and start a career in financial markets. - Sales Representative Bloomberg Employee Review

4.0
May 7, 2012
Recommend
CEO approval
Business Outlook

Pros

-great, energetic people -free food -great learning environment -plenty of client facing exposure -work with a huge variety of people -with so many departments, there is a lot of support

Cons

-too many projects prioritized at once -flat organization -management is sometimes promoted by friends and don't really know how to lead others -management in different departments need to communicate more and agree for the best of their teams and clients

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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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