2 min readfrom Data Science

How do you keep up without burnout?

DS sometimes feels like there's infinite amount of things to learn. Most recent trend has been AI engineering

And it's not like AI came in so you can deprioritize something else, but instead it just gets added to the heap. So you already had this massive amount of content to know from stats & product, trad. ML, deployment, ops, engineering, cloud, etc. and then you add the new thing on and the new thing. And when you read the job descriptions they literally list of all of this. I just had an interview for a random gaming company that wanted cloud, snowflake, stats, ML, ops, and AI experience in 1 person and it was for like 3-5 years of experience. And I wish that this was a one off thing but it seems to get more common.

It actually feels like FAANG is easier to interview for because they silo people and not expect you to know and do everything

What is your strategy for learning these skills without getting exhausted, or do you feel companies expectations are overflated? Is this a by product of AI where people are expected to do a lot more with less?

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