Great Company, Terrible Management - Recensione dipendente - Client Service Specialist presso Bloomberg

1,0
6 nov 2024
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

Company Benefits & Office Perks

Svantaggi

Workforce Bullying and Harassment I observed and experienced behaviors that fell short of fostering an inclusive and respectful work environment. This greatly affected team morale and, at times, made it difficult to focus on delivering my best work. Limited Responsiveness from HR I sought support from HR where necessary, advocating for a healthier team dynamic. But HR did absolutely NOTHING. I experienced retaliation from my managers and HR. Also my manager TOLD the person I reported that it was me because they had a VERY close relationship. The resolution process with HR was highly ineffective in addressing workplace issues. This occasionally left me feeling unsupported and contributed to a sense of frustration among team members. If they don’t like you they will put you on a performance plan ASAP or offer you severance so you do not become a liability for the company.

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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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