Slow, disappointing and few positives - Analytics Representative Bloomberg Employee Review

2.0
Aug 6, 2011
Recommend
CEO approval
Business Outlook

Pros

- Good introductory training - Opportunity for further training - Opportunity to advance relatively quickly into new roles - Some very intelligent/knowledgeable colleagues - Free Bloomberg Anywhere

Cons

- High percentage of colleagues are incompetent - Management induce a condescending culture and treat employees like children - Management seemingly spend countless hours devising new methods to irritate employees - Leadership roles are only offered to people who have no words in their vocabulary beyond 'yes, of course I can do that for you'... regardless of how ridiculous suggested request may be - Management bend over backwards for the sake of rigid, poorly designed metrics regardless on the impact of quality of service - Promotions are not remunerated immediately, you must await a pay review - Pay reviews are based on poorly designed metrics - Pay is extremely opaque for a firm that prides itself on transparency

Explore other reviews about Bloomberg

5.0
Jun 25, 2026
Recommend
CEO approval
Business Outlook

Pros

great company to work for

Cons

I cant think of any ons

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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