Genuinely a great company - very underrated - Recensione dipendente - Financial Product Analytics and Sales presso Bloomberg

5,0
30 dic 2022
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

- Bloomberg literally pay you for your first 6 months to study and then following that they are willing to sponsor further learning be it a masters, CFA, CAIA, etc. - in Analytics specifically you learn a lot in a short space of time - The working hours are not nearly as bad as in other financial firms. - Unlimited pantry snacks - The office is a lovely space I think people generally do have misconceptions about the opportunities here. Yes it’s not a full on financial firm however if getting there is your end goal, Bloomberg can certainly help and is a great place to start

Svantaggi

- In your first 6 months you can’t work from home. After 6 months you get 1 day WFH and 2 days after a year. - more than your day job is expected of you in terms of participating in philanthropic efforts which not everyone may care for

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

Vantaggi

Great company, in this role you have the chance to learn about the financial markets, the terminal, and also you get client exposure.

Svantaggi

Not really cons, culture is great.

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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