Here's what I did before making this video
I was at home watching kpop videos when suddenly I thought useless and pathetic because I just spent two hours watching 4 girls say I
Needed some sort of confirmation that I was still wanted and loved in this world so I called my mom
She didn't pick up
She never does so I need a new way to feel validated and my next best thing
my data science skills
I needed to feel wanted so I refat my resume brushed my hair and applied to all these data science analytics positions
I whispered to myself. Tell me you want me I
Quickly learned that takes more than 20 minutes to get an interview
So I unbrushed my hair took my pants off and went to bed soon. The interview started flowing in one phone
Call two phone call three phone call
Rejection. You win some you lose some I started getting on-site interviews one on site two on site three on site at
Every interview I whispered to them. Tell me you want me some did some didn't but I had what I need
I'm validated and here is what I learned from all these interviews
Pull up
So for the technical interview, this is basically just a simple SQL or sequel
Question or it can also be a simple coding question like Python or something
and the reason why they ask you this question is to make sure that you know how to write queries because you're gonna be doing
a lot of that on the job
And also if you can work with a simple program if you could write simple programs nothing too complicated now
Not gonna lie this part of the interview or this interview is probably going to be the easiest out of the data science analytics position
So, let's see if you can solve one of these questions. Here's an example
So here you have a table called publisher info that has all the information about a publisher and the videos
They publish and then you have the consumption info where you have all the information of user consuming a single video
so two questions one how many minutes worth of video does an average publisher have
Two how many publishers have at least one user who watched their videos? I'll give you ten seconds to finish it
DDT
So here's the answer obviously in a real interview there would be more follow-up questions since it's an hour long
But let me show you how I studied for it
I locked myself in a room and open cracking the coding interview and finish all the questions until chapter 5 or until I feel like
Puking after that I go to all these websites to practice sequel questions
And of course I go on Glassdoor comm to see if we could find it in juicy unique tech questions
The math interview are sometimes they call it the quantitative interview
This one is quite simple also because they just ask you some simple probability questions or some simple descriptive
Statistics question, so here's an example
Geomatics an STD test and the test is advertised as being 99% accurate if you have the SCD your test positive
99% of the time if you don't have the STD you will test negative
99% of the time if
1% of all people have this STD and Joanne test positive. What is the probability that Joma has this disease?
I'll give you a few seconds to answer this Russian tic-tock. Tic-tock. Tic-tock. Tic-tock. Tic-tock tic-tock tic-tock thing
So the answer is zero because you have to get late to get an STD
Anyways, the right answer is 50% and you have to use Bayes theorem
So if you went to college and you listened during your freshman year, these concepts should be pretty familiar to you
But then again, that's only if you remember them, so here's a list of things that they would ask you about
So like conditional probabilities Bayes theorem
binomial distribution normal distribution
descriptive statistics and like understanding the law of large numbers
Central limit theorem and linear regressions. So if you understand these concepts, that's pretty good. And you should be fine and then for me I
Wasn't fine because I didn't listen
So what I did to study for that
I went back to my old textbooks
Read some of these chapters and then refresh my memory and then also I did some practice questions
Especially for probabilities because sometimes it's a little bit tricky. It's almost like a brain teaser
So you just got practice just like quoting the product interview now
This is a little bit subjective, but it's important get right
They will ask you a hypothetical
Product and how you improve it?
And then they will also ask you. What metrics would you track to measure its success also?
They're going to give you situations where there are trade-offs between metrics and you have to argue which one is best for the product
It's not always black and white. We just want to know how well do you work with data in?
the products perspective
So it's kind of hard to give you an example of a question because usually it's like a back and forth and a conversation
So here's an example of what the interview will look like. Alright, so as you know not vine is a platform where users can share
6.1 looping videos as seen in the startup series and it's basically a feat of content you follow now
Imagine we are considering launching a share button where you can share someone else's video and it will show to your followers
How would you evaluate this change? What metrics do you expect to change and how will you decide to launch it or not? Hmm
Well, we can do an experiment roll out to only a few publishers first and then a be tested
So for some users, they see it and for some they don't see the shared post
That way we can see the difference in consumer behavior. For example
Inventory will probably go up because of that
We will see if it increases video watch time per person and if it increases retention from users with this feature
We also have to make sure it doesn't cannibalize the original content
so even if they have more video impressions
We want to see if the view per impressions didn't decrease too much which can mean they don't care about the shared videos
we can also run surveys to survey them if they enjoy watching this shared content, so
so product questions are like that but usually with more follow-ups and more deep dives, but you get the gist so obviously this is a
generalizations of all the data science interviews
I've had some are harder. Some are easier
but if you are able to answer these question your chance of getting a data science job is
Higher with statistical significance than if you weren't able to answer these questions
By the way, this video was sponsored by brilliant org
which is kind of cool because I actually used brilliant or when I was applying to my
Untitled large company since the company gave me links to help me prepare for my interview and one of the links that they gave me
Is a bunch of combinatorics questions aka probability questions on brilliant org
It really helped me on the math part of the interview because I was killing the probability questions
I actually find it really fun to crank out these questions
It makes me feel good about myself and keeps me sharp, and they're good brain teasers for interviews
especially for data science of quantum
Very good supplement to my interview preps so highly recommended
Also, if you're in school, you can supplement your learning by using this website because there's a wide variety of topics
which is pre-built because I love the UI on the website and it makes studying so much more fun with their quizzes if
You're interested. There's a link in the description down below. Best of all you can get 20% off their premium subscription
So you two you can kill it at the interview for the large on type of company
alright
I hope you enjoyed this video or I gotta go now
Cuz I'll have to figure out how to make food because my roommates are gone. I've been eating Cheetos for like the past two days
But yeah
Almost