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      Bloomberg

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      You'll be micromanaged to death - Financial Sales and Analytics Bloomberg Employee Review

      2.0
      Mar 28, 2017
      Financial sales and analytics
      Recommend
      CEO approval
      Business Outlook

      Pros

      Good starting salary, extensive training, great colleagues, free snacks.

      Cons

      Where do I start... - Clueless team leaders who have no idea of how to manage and motivate people. - Absolutely no scope for creativity, you have to follow very strict guidelines which quite often don't make sense. - Micromanagement - no matter what your job title is and how senior you are, if you are 5 minutes late from your lunch break, you'll get a lot of stick for it. - Working hours are long - you have to be in the office from 8 to 18. Very limited career opportunities - preference always goes to external candidates. Overall, it's a good company to start your career at and it looks good on CV but not that many people stay.

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      5.0
      Jul 10, 2026
      Quantitative developer
      Recommend
      CEO approval
      Business Outlook

      Pros

      Great work-life balance with nice benefits and interesting client work

      Cons

      A bit slow-moving in terms of AI adoption for internal tools

      4.0
      Jun 28, 2026
      Data management professional internship
      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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