Role Growth, but no Career Growth - Recensione dipendente - Global Data Analyst presso Bloomberg

4,0
3 ott 2019
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

Medical Benefits Lateral movement Free Food Good Working Environment Encourages collaboration

Svantaggi

You can progress your role into manager and even higher but if you plan to have a career in finance or quantitative analytics, it might be a challenge or will take a long time. Your role can progress but your career will be stagnant and be stuck in customer service. Admin/Customer Service disguised as "Analyst" Job. Claim to be a tech company but relies heavily on Excel. If Microsoft takes out Excel, Bloomberg will shut down along with the world market that relies on Bloomberg data. Not a finance job but a financial product ambassador; people do modelling and financial analysis but it is just to make "clients" have ease of use and show more functionality for the terminal. Analyst/Analytics here is synonymous to knowing what the client/customer needs and not necessarily include any quantitative analysis. Might be less than 5% that quantitative analysis will be required for an Analyst job.

Esplora altre recensioni su Bloomberg

5,0
25 giu 2026
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

great company to work for

Svantaggi

I cant think of any ons

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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