Hey, What's up? today I got Richard
The CEO and founder of Leap.ai
a platform that helps you use AI
to make your job search 10x easier, 10 faster
and today he's going to show  us
How to get a job in data science
and Richard has hired over 500 people at Google
so I don't think there are so very many people in the world
as qualified as him
to tell us how to become a data scientist
so i'm going to ask him
4 key questions to keep this interview organised
first question that Richard is going to answer is
do you need a degree?
well, on book, you don't.
many companies will say you don't need a degree
but in reality,
i don't think i have seen any data scientist
who does not have a college degree
so it really depends how you want to take it
so it's possible, but you are saying you never seen it
actually happened. all the data scientist you have met
have a degree and do they have
a PHD, a masters or just a bachelor's
So what I have seen is... I don't have seen anybody
who does not have a degree
the reason why...
i have seen a bunch of software engineers
who does not have a degree
Why? software engineers, you just learn
more like a practical use
of programming language then build some stuff
but for data scientists, you do have a lot of math behind it
without going to college, it;s hard for you
to fully comprehend
those science behind it
so that's just a little bit  practical
theoritically you can
but in reality, you have to comprehend 
those maths behind it
in terms of degree, yes indeed i see a lot
PHDs and a bunch of masters
probably there's also some bachelors
if you have experience,
honestly, degree doesn't matter that much
which bachelor should someone get?
and which masters, PHDs should people get 
if they want to become a data scientist?
what is the best one?
ofcourse, it's Statistics
there you go, perfect!
it would be nice if there's a data science masters right?
but maybe that will be coming to colleges soon
so that next question is...
what do you think of data science 
bootcamps?
one of them being galvanized, and i think
there's a bunch of data science bootcamps 
popping up especially in San Francisco
and New York now
absolutely, they are very helpful
and ofcourse, the best situation is that
you get to work on realtime projects
you can also go to companies
apply as an intern
work as a volunteer as a data scientist
but if you don't have those type of opportunities
but if you have some science foundation, 
you can still go to bootcamps
then you really learn those type of things
paired with your science foundation
you can be equipped with that stuff and go to interviews
i think we are talking before the interview
that my friend, he went to a 
data science bootcamp
and he's able to get a job
and he got multiple job offers for data science
would you say that, there's a lack of
data scientist and there's more demand
than there are data scientist right now?
ofcourse
aboslutely
data science is growing so much faster
than anybody antipated
with a ton of data scientist need
and also more challenges
the industry doesn't know how to evaluate
data scientist
starting from google, from facebook
people figure out the mechanics on how to
evaluate a software engineer
but data scientist, the people are still
figuring out how to evaluate 
who has the potential to be a great data scientist
so by the way, 
anyone out there, if you want
a high-paying technical career
and you studied
something like chemistry, biology, physics
and you have a scientific mind
and you may have a degree
and couldn't have a good job afterward  
and i think that happens 
that's a very common problem right?
i've seen so many people who studied 
chemistry, biology, physics
4.0 students, cum laude, suma cum laude
and yet they can't find a job because there's no
demand for their skill
do you think going to data science bootcamps
is a good alternative for them so that
they dont have to re-learn the math right?
in those science class you go all the way up
to linear algebra so they kind of started
data science with a step forward
Absolutely. you definitely need to have a 
science foundation, especially the math foundation
go to bootcamp
and at the same time, you can find some
real life projects
you go to work with a company
as an intern or as a volunteer
you can get real-life experience, and you will be good
alright, that leads to our next question 
we covered over what happens if you
are kind of screwed by studying a useless
science degree
i'm sorry about that but it's kind of true
it's hard to get a job as a biology major
i don't critic the job market, it just says
question number 3
if someone is brandnew, just graduated 
from high school, 18
what's the ideal path for someone
who wants to get a job doing data science
for company like google or any other
first tier tech company?
That's easy. The first thing is to go to
a college to study stats or computer science
incase those two department feel overly competitive
then you can get into some other science
major that you are really interested
that's number 1, just get into those majors
number 2, try to do as many internship as possible
and i said it before
while you are in sophomore or junior,
try to do internship even if they don't pay you
that's okay
be a volunteer
working on real life projects
is way more important
not what you learn from class
even for software engineers
work on real life projects, that is number 2
number 3 is basically when you graduated 
you feel you don't have enough experiences
attend some of training camps
or you use whatever is your skill
to get a job within the company
improving your skill to be a data scientist
from what i've seen, we interviewed someone
previously on how to get a job in machine learning
for anyone out there
would you say machine learning is a 
sub section of data science?
is that true?
machine learning is more focused on algorythms
data science is more focused on data
and insights
and paired with algorithms to get the final results
so it's two differnt roles?
yes
when it comes to data science,
by the way, i'm learning something here
that's why i did the interviews
because I thought
machine learning is a sub-section of data science
people may want put it in a different way
so you asked me
i see it this way, and other people may 
have arrived in a different way but all of this is fine
What could get someone an edge
when they are applying for an internship
or their first job above other 
students or other graduates?
the general sense when applying for any job
demonstrate that you have the potential 
to be the best in the category
if you are applying to be a software engineer,
demonstrate that you have the potential
to be the best software engineer
if you are applying to be a data scientist
demonstrate that you have the potential
to be the best data scientist
question number 4 that we have
and perfect segway which is
what does it take to be a great data scientist?
i think data scientist is one domain
that people needs to understand
people are still trying to figure out 
generally, what i have seen is, number 1
data scientist should love data
they should be passionate about data
number 2, unlike many other things
you have to generate unique insight
unlike for software engineers, for example
 Matt write some beautiful code
and i use it for 1 case
i copy his code and use it for another case
i created avalue
but for the same data, Matt absorb other insight
and i absorb the same insight, i dont add value
basically, you should have the capability
 to see data and get some unique insights
do you think that's a little bit of psychology
that goes into that because usually the data
you're observing comes from people right?
is there some psychology that you are 
trying to figure out what the users are doing?
we definitely somehow have experience
definitely your experience
how you see the word
but in reality, data scientists spend 90%
 of their time cleaning data
you just need to get the data
massage the data
make the data in a lesser form
then spend the 10% of the time
to pair with algorithms and get the final results
a data scientist should have the patience to clean the data
and ability to debug
it's kind of like software engineers
spend 90% of  their time debugging
that's true
what do you mean by cleaning the data?
so basically, you look at the data
analyze it
so you have to identify them
either you excluded them or you fix them
awesome!
Thanks Richard for sharing insights
on getting a job in data science
and becoming a data scientist
if anybody out there wants to use AI
to get a job in data science or get any technical job
and also get a job in UX/UI
or any of this dev roles
Leap.ai uses AI to
help you land a job. make it 10x easier,
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you get $500 if you land a job
thanks, Richard for your time, it's been a lot of fun
Thank you Mat
