A solid stepping stone to a career in technology or finance - Global Data Analyst Bloomberg Employee Review

3.0
12 Jan 2021
Recommend
CEO approval
Business outlook

Pros

Excellent Benefits (most of which disappear in a pandemic) - free food, young community, tons of clubs and activities, Princeton nightlife can be decent Decent foundation for a career in finance or technology

Cons

Compensation is decent out of college but raises and bonuses are low Very difficult to get promoted unless you are on the right teams (determined during interviews). If you are not placed on the right track, career growth is extremely difficult to attain (as well as bumps in compensation) Long hours doing some monotonous, often meaningless work. Management is always changing directions and projects rarely go full circle Recognition for good work is hard to come by. Some departments have toxic management that says bad things about their employees and managers behind their backs

Explore other reviews about Bloomberg

5.0
22 Jun 2026
Recommend
CEO approval
Business outlook

Pros

Good management + good people + work life balance

Cons

NA - can be stressful

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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