Just to clarify: different banks name their teams differently, and they are massive organizations where internal and external consistency in naming is sometimes lacking. For example at GS you might have strats and they do a full spectrum of things. At MS they have strats and modellers where strats are more desk aligned. At JPM they have global quantitative research and quantitative research, where the teams have nothing to do with each other and the former is a subteam within research (in the sense of equity research) and does not offer the kind of technical modelling/strat role you'd find in the latter. Applying to an equity research role, no quant (it's a term covering so many roles it's almost meaningless, but hopefully it is clear what I mean here) will have seen your resume (again, massive organizations and things are not usually as well organized as they may appear on the outside at first glance).
Good to know!
Path 1: Finish my Masters (~9 months left) and aim for a good grade + do freelance work which is Python/Data Engineering/Data Science/ML focused. Then apply for Strat/Quant Dev roles and go from there? No need for CQF or otherwise.
Path 2: Finish my Masters + remaining in FAANG is an option but the role in FAANG is not really helping me get to the level I need in Python for quant dev or Strat roles - if anything its setting me back because I'm spending more time on SQL and silly stuff vs actual programming and cloud work. I could then apply for Strat/Quant Dev roles but do not see what changes spending another 9 months there (instead, won't I look too senior, as I would have about 6 years experience then).
Path 3: Finish my Masters + pick up a contract role at a bank / financial services industry as a Data Engineer / Python Dev or similar which sits in the FO. Try to convert it to full time.
Out of curiosity, I came across an article on traders, and how they need to know Python nowerdays. I wonder if that would be a fit? Or I've missed that boat already?