Data Science/ML roles in Finance vs Tech
What is preferred between Data Science/ML roles in Finance vs Tech from long term perspective. Background: Currently: Pursuing MS in CS (From one of the ivy's) Dependent on H1B sponsorship after graduation Couple of intern offers : Both well paying (above normal SWE intern stipends). First role is Data Science Intern at AI lab of an Investment bank in NYC (mostly NLP related work) Other is MLE role at good non-FANGM tech company in Seattle. Pros of Finance offer: Might be easy to get a return offer If H1B does not come through after full time, good chance of re-location to other non-US regions. Pros of Tech offer: Good learning, latest techniques of applying ML practically and building ML pipelines
Tech over finance
Any specific reason why ?
Cause tech pays more and traditional finance is dying. You can hear major investment bank ceos (including mine) calling the future as coders who can trade rather than traders who can code.
I am a DS in finance. Go to tech. In finance, you will be either forever second citizen or always behind what tech is doing.
Thanks, H1B and work wise? Do you feel you don't work on latest tech stacks and all ? Also, does it matter if the AI lab in finance is pretty selective and takes very few interns every year ?
We use tensorflow and python but nothing compared to latest development from tech. H1B is easy to get in finance, and WLB is also good. You just get treated as second citizen compared to quants with background in FE. Don’t know much about AI lab.
MLE career trajectory is higher.
Aren't MLE jobs limited compared to backend ? Also nowadays everyone is doing ML. So does it not increase the demand for Backend in future ?
@Salesforce MLE is not being done by everyone. DS is being done by a good chunk of people. There’s an insane demand for MLEs and DEs