Surprisingly inflexible for a tech firm culture - Analytics Bloomberg Employee Review

4.0
Jun 12, 2018
Recommend
CEO approval
Business outlook

Pros

- young crowd and will make lots of friends very quickly who will help/support you through thick and thin for many years to come - tech vibe, open floor plan, easy-to-approach senior management - very structured work day and clear idea of what is expected of you; easy to succeed if you are good at following instructions - abundance of resources to self learn about a variety of different topics - great employee benefits and perks

Cons

- inflexible schedule, in Analytics your schedule is literally clocked by the hour; your badge-in and badge-out time is recorded and shown on your bio page - mediocre middle management - you will get very bored with the structured day after a few years and the alternative is zig-zag career progression - if you want to feel like a market participant, this is not the firm for you -- most market players don't take Bloomberg very seriously

Explore other reviews about Bloomberg

5.0
Jun 1, 2026
Recommend
CEO approval
Business outlook

Pros

Free food, good salary, incredible Pro Bono opportunities

Cons

Lack of flexibility around RTO policy

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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