Great Starting Place/Ending Place (for Finance candidates) - Sales and Analytics Targeted - Financial Sales and Analytics Bloomberg Employee Review

4.0
27 Oct 2013
Recommend
CEO approval
Business outlook

Pros

-Great people, all are friendly, young and enthusiastic -Great place to learn finance from scratch as training program is one of the best of anywhere -Snacks -Best work life balance -Good compensation if you "meet expectations" -Name brand recognition and very good experience with the software -Best benefits of anywhere -Can transition to ANY role within the firm -Great place to have a start to end career with good support behind you -Everyone listens to your ideas and encourages you to act on them

Cons

-Do not work a finance job; this is a technology company first -Compensation is not built of effort or experience but rather of how long you have been in the company -Very poor compensation advancement structure -Lack of career progression -Difficult to transition to a different job (in finance) due to lack of useful experience -Career/Experience is very heavily dictated by your manager -No freedom in time management; everything is dictated what you need to do by the minute -Potential to get stuck at your current role

Explore other reviews about Bloomberg

5.0
25 Jun 2026
Recommend
CEO approval
Business outlook

Pros

great company to work for

Cons

I cant think of any ons

4.0
28 Jun 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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