If you're on the right team, Bloomberg can be very rewarding - Financial Software Developer Bloomberg Employee Review

4.0
7 Jan 2014
Recommend
CEO approval
Business outlook

Pros

- If you land on the right team, there is a lot of flexibility and great work-life balance. Fortunately, the percentage of the "good" teams is growing steadily, especially within the Derivatives and Infrastructure departments of R&D. - There are a lot of opportunities to grow professionally, but you need to forge your own path. - Very intelligent colleagues, great ideas - Free snacks and drinks/juice all day everyday - Excellent compensation and benefits

Cons

- A lot of red tape (as with many large and successful corporations), meaning that great ideas need a lot of persistence to really take off, or else they will be swept aside for the next money grab enhancement. - Some old technologies and implementations are so established that they're tough to supplant with smarter/faster/newer ones. - Open floorplan. While it fosters collaboration, concentration is very easily broken

Explore other reviews about Bloomberg

5.0
6 May 2026
Recommend
CEO approval
Business outlook

Pros

Great place to work if you are looking for work life balance

Cons

The data department has very limited growth opportunities

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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