Continuing growth opportunity - Recensione dipendente - Product Manager presso Bloomberg

4,0
11 nov 2025
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

- Continue to learn and grow after 10 years - Great people to work with - Inclusive culture and focus on philanthropy - Growing product culture - outcome focused - Very international and customer-centric company

Svantaggi

- Not all those who get promoted are qualified for management - 4 days in the office, when wfh works perfectly fine - Very subjective who your peers are, what your expectations are as an IC and what good is meant to look like

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5,0
22 apr 2026
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

Great culture, benefits, pay, and work-life balance

Svantaggi

The technical challenges can be a bit stagnant. You learn to deal with people rather than systems

4,0
28 giu 2026
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

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.

Svantaggi

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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