u/LeaguePrototype

I get ask the question online and in person: what it takes to get into a good FAANG company?

I spent the last year working at a Google as DS and spent the previous 3 working at random industries (pharma, supply chain, large buy-side banks, etc.)

I genuinely think that the quality of DS I worked at in FAANG were higher caliber for the following reasons:

All my teammates weren't necessarily experts at a lot of things, but they had a very good grasp of the fundamentals. If you take the DS skill tree divided up into categories (ML/coding, communication, business/product sense, etc), my teammates were at least a 7-8/10 on all of these while being expert level at some things the team was responsible for. While doing mock interviews, what stood out the most is how badly some people commuinicate . I understand that a lot of people working in STEM have English as a second language, but that's not taken into considerationg when evaluating if they want to work with you. Also, I worked with a lot of DS that score very low in some aspect of what I would consider 'fundamentals'. Some knew how to code and develop, but never took a probability class. Others had heavy math background and had no idea what to do outside a notebook. Others had a good industry experience but weren't sure how to quantify their ideas and turn it into a stats problem. At Google everyone could reliably do everything to an acceptable level, and learn how to do it better if they needed to and everyone had a good 'vibe' that made them fun to talk to and work with. Honestly, the best part of the job were the coworkers while the work itself was pretty boring.

I think I was picked for the role since it was a communication heavy role and I had a lot of experience coaching people and public speaking

To land a job at these companies I don't think you need to be an expert specialist for the large majority of the positions. I think what you get evaluated on is if a DS problem is thrown at you, or you are in a discussion about a problem, you know what is being discussed, how the problem is solved generally, or know what to look up to solve it. If you have the extensive knowledge and experience + the things listed above you'll likely get promoted to Staff level pretty quickly or hired there.

So, my final thoughts is if you are studying for these positions, don't spend your time deep diving into niche topics or doing quant style problmes. Instead, have a very good baseline understanding of the fundamentals of what DS does and be able to communicate well and demonstrate that you can contribute.

For companies that can be highly picky (FAANG, MBB, etc) you also need to pass the airport test: How would I feel if I was stuck at an airport with you waiting for my next flight?

Just had another FAANG interview, and the questions weren't that difficult but something happened to my brain midway and it kind of felt like I was getting exhausted. I still got the answer right, but after fucking around for like 5 minutes doing dumb shit

Does this happen to anyone else or just me? The questions aren't hard that, but the mental battery of the questions one after another gets tiring and 3/4 way through you aren't that sharp anymore? I have to solve the problem, explain my thinking in a charismatic way, make sure we are on the same page, and get the problem correct

I might just be retarded, or do you struggle through this as well and have some tips?

My interview experience has been a massively varied at this point, but what I've noticed is the massive difference between big companies like FAANG and smaller orgs like DS in banking or random small companies

At FAANG it's kind of like an IQ + knowledge test (what google calls Role related knowledge) and smaller companies do assessments for very specific types of modeling or use cases, like build a model being evaluated on a certain metric.

So at FAANG I was asked questions like "why is the formula for s.d. different for pop. vs sample', or 'what happens to the bias/variance in x,y,z situation' mean while at companies that are smaller and pay less they sent me a random 30-60 minute assessment and asked me to directly clean data and code up a model with sklearn/pandas.

Is this what everyone else has experienced? It does seem like at smaller or traditional companies test if you will be a good code monkey while others look for actual understanding.

I’m currently spiraling trying to plan my next trip and I’ve realized there are basically four types of people. I'm curious which camp you fall into or if I'm just doing this wrong:

1. You pick the place first, build the budget after, and then figure out how to save for it.
2. You save a specific "travel fund" first, then see what trip that amount can actually buy you.
3. You have a "reliable" spot that you go to every year because the math is already done kinda of like what older generations did.
4. You check your Chase app and book a flight before you can talk yourself out of it.

I find it incredibly hard to bridge the gap between "what I want" and "what I can actually afford". How are you all actually doing this?