Specialist - Sales and Analytics Bloomberg Employee Review

1.0
Mar 19, 2016
Recommend
CEO approval
Business Outlook

Pros

The company provides thorough training opportunities, but to be honest, they are only useful for non finance major students, very basic knowledge that every finance major would have known in college. The company claims they have great corporate culture, which may be true from some point of view. Colleagues can be supportive sometimes.

Cons

Low efficiency in work. This company has very mature and profitable business model, which should be a good thing. However, it also leads to low efficiency and lack of creative spirit (ironically, "creative" is one of the core corporate culture). You always receive warm welcome for your new ideas or proposals, but that's it, no more, just welcome, no followup, no execution. They prefer to do things in the old way. And many proposals and projects that do get into the execution phase are very pointless.

Explore other reviews about Bloomberg

5.0
Jul 16, 2026
Recommend
CEO approval
Business Outlook

Pros

Great benefits and people are very supportive

Cons

Flat hierarchical structure is tough sometimes to crack

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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