Netflix DS WLB and Performance Reviews
Looking for an honest take on WLB and performance reviews for DS at Netflix. I have experience in the FAANGs known for terrible WLB and competitiveness during performance reviews and I want to understand how Netflix compares. For example, in your experience, how many hours does the average DS at Netflix needs to work weekly to get a solid meets all, with minimized risk of being fired, in performance reviews? Yes I understand prioritizing and working smaller but I want a rough measure of WLB. TC: ~$300k #data #datascience #datascientist
These poll answers are not coming from Netflix employees. You certainly need to produce. But you don’t need to get there 24/7. The place gets pretty empty after 5:30 so wlb is definitely something the company takes to heart. While every manager is different, it’s certainly a chill environment.
Yeah place gets empty but it's pretty much an open secret that everyone works on their free time and many weekend mornings, all in the name of "freedom and responsibility"
Do you have a sense of how it compares to Meta? I worked there and found the competition and WLB suboptimal but completely fine.
@net, what to expect on initial phone screen with recruiter?
Given that your poll has 11 choices with meaningless cutoffs and that you're unlikely to even get that many Netfix data scientists to read this, I think you should worry less about working hours and more about improving research design skills if you want to succeed at Netfix.