Good people, decent work-life balance, high intensity and high micromanagement - Financial Product Analytics and Sales Bloomberg Employee Review

4.0
Mar 6, 2021
Recommend
CEO approval
Business Outlook

Pros

Great colleagues, good pay for the job, great benefits and pantry. Great opportunity to learn about different player types in the finance industry and what they do from a third party perspective. And of course, a great opportunity to learn how to use the Bloomberg Terminal. Good work-life balance too, usually you can leave work behind past 6pm. The intensity of the work is quite high (can be a pro or a con depending on what you like) - you have to handle multiple clients at once and some days the volume of queries is high (more of a con)

Cons

Micromanagement + excessively stats driven.... nature of the job is customer-oriented and micromanagement is done to ensure enough coverage. The reason for such a management style is understandable, but it does take some time to get used to, and hard to say anyone likes this style of management. This is not to say the managers themselves are bad people though, they can actually be really nice people, who are just forced to manage this way by the system.

Explore other reviews about Bloomberg

5.0
Jun 25, 2026
Recommend
CEO approval
Business Outlook

Pros

great company to work for

Cons

I cant think of any ons

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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