Welcome to 80s - Software Engineer Bloomberg Employee Review

1.0
Dec 20, 2017
Recommend
CEO approval
Business Outlook

Pros

If you miss 80s (and I don't mean the music, but processes, culture, and technology), Bloomberg is the company for you. If you miss 90s, wait a bit, they are getting there, come in a decade or two. To get a good understanding of what to expect, listen carefully about the company's culture, but remember that in 80s those words must have meant something different: "Flexibility" means "Manage your time yourself as long as your manager can constantly see you". "Flat structure" means "open space" or maybe "flat vertical structure". "Hard-working" means "Keep yourself busy till late". "Agile" means "Micromanagement". "Innovation" means "NIH syndrome". "Risk-taking" means "If you screw up just this much ...". "Be bold" means "We've no idea what that means, but they mention it in every book".

Cons

If you are looking for an internship or your first job, and money is your only motivation, then go to Bloomberg.

Explore other reviews about Bloomberg

5.0
May 6, 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
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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