Collaborative culture but slow progression and potential traps - Data Scientist Bloomberg Employee Review

3.0
Jun 17, 2026
Recommend
CEO approval
Business Outlook

Pros

* Collaborative culture and the overall friendliness across the company * Internal prospect if you are committed to the company culture

Cons

* Mostly 8-6 in roles that's not fulfilling for the most part * Could be a trap if you stay for too long * Skill growth may only be relevant to the company and not transferable in the long term * Mixed group of contributors who are stuck/committed to the company and have been moving/moved around to different departments in roles that might not be the most suitable * Progression in the first view years could be slow - mainly applicable to the back office * Exit interview felt out of touch. To my surprise, it was held virtually and only seem to care if my departure was due to "management"

Explore other reviews about Bloomberg

5.0
Jun 11, 2026
Recommend
CEO approval
Business Outlook

Pros

Great company, in this role you have the chance to learn about the financial markets, the terminal, and also you get client exposure.

Cons

Not really cons, culture is great.

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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