today I'm going to talk about my journey into data science and how i became a self-taught
data scientist but before i do that i feel like i need to address that gap
that um in my youtube video and why i haven't been consistent first of all i just want to say that
i'm a little bit nervous because i am recording a video a youtube video um after i don't know
six months when i was active on youtube a couple of months ago i think i did a few things wrong
one was that i was thinking that i need to dress up i need to do my face i didn't need
to do my hair for every video so um and over the last year staying at home and being in
quarantine i realized that i don't like doing any of that the second thing that i was doing
wrong is that i was over editing my videos if you have seen my old videos you would see like
i would edit a hell out of them even like me breathing i'll remove it
but honestly like that was exhausting that took me that made my editing process very very long
it would take me more than four or five hours to edit edit one video um and that just became
very very time consuming and so i decided that i don't have time to dedicate to a youtube account
so i took a break um and not just youtube i actually took a break from a lot of other things
uh for example public speaking i've not been doing a lot of that just last year staying at home and
working from home uh while navigating live has just been pretty challenging um but i got inspired
by one of my co-workers who also has a who has multiple youtube channels he and i were talking
and so she really got me excited about youtube again she's doing pretty well on her channel
so i thought now well maybe i have a friend i can talk to somebody about like editing and all that
behind the scenes that goes on for youtube channel and we can share text with each other so
i'm back and with that let's jump into how i became a data scientist
my journey coming from a non-tech background if you like what you see make sure to give this video
a like that's how youtube algorithm is going to know that this is useful and subscribe if you
want to hear more from me so before i talk about how i became a data scientist i need
to tell you a little bit about my background my educational learning i actually have a six-year
gap between my high school and my quality education for personal reasons family reasons
cultural reasons i'll not go into detail so when i was starting my educational journey back again
computer science or tech or data science wasn't even an option because i didn't even know that
these existed i didn't know like people can work for their computer which is it's mind-boggling
to me that why didn't i know all of that and i i know why i didn't know because nobody in my family
was part of tech and i was exposed to different job families different industries while growing up
when i went back to school i ended up choosing business as my major i went to university
washington and one of the classes that i took was information systems and that class
basically exposed me to the world of beta as soon as i took that class i immediately knew that this
is exactly what i want to do i was looking for internships i couldn't find an internship uh in
the data science because like there was nothing like even the data analyst position did not exist
uh this was back in 2012 2013. so what ended up happening is that i went to this networking
event where there was uh amazon was present and for their financial analyst program um and i i
did not consider applying for that however while talking to somebody at the networking event from
a big one of the amazonians he basically convinced me he said if your interest is data this would be
a really really good internship for you it's very technical so like okay i handed him my resume
amazon internships were super weird at that time they were about like the financial analyst
internship was about i ended up six months long and then i ended up doing two extra months because
the team needed help so i was like okay i'll i'll be making money anyway so like um it's more work
experience for me the internship was great i got the amazon exposure i got the big tech name on my
resume however i did not really enjoy working as a financial analyst there was a lot of repetitive
work like dashboarding refreshing the data and like every monday i would have to make sure that
the weekly business review that's already um and then like if there's somebody has questions
in terms of like why this data is going up or now like i would have to answer i just did not
enjoy doing that type of stuff i almost gave up on the data
the other world but then i ended up meeting with somebody who worked as a data engineer at that
time and they kind of like walked me through what they did day to day um and that got me interested
so what i did i finished my internship i ended up taking a bunch of data engineering focus courses
um at the university of washington outside of business school because i wanted to explore that
area a little bit more um i took i believe i took three courses over the summer
and eventually i knew enough that i could pass a technical interview so also like while interning
i made a lot of connections within amazon and um had interviews lined up so i interviewed
with three teams i got offers from two for a data engineer then i started working as a
data engineer so i did that for about two years building up pipelines for all the traffic teams
uh at amazon so traffic they used all the traffic they have changed the name since then so traffic
pretty much means basically how customers who when if you go to amazon.com like which channel are you
coming from are you searching on google and then clicking on something and then going to amazon
or you're seeing something on facebook and then you're going so basically trying to figure out
like how customers are entering that amazon.com domain did that for two years i kind of started
feeling comfortable in the space so and i did one project in search focus and that was the
point where i was like okay this is exactly what i want to do and i wanted to go more into the data
science domain so i ended up looking for different teams i finally found one team that was very open
to having me a data engineer be part of their team and get exposure to data science and then learn on
my own and then like do some projects uh while i learn so that's exactly what i did i joined the
team the manager uh i wanted to be a part of the manager who helped me he was amazing he basically
uh he basically guided me he would tell me books if there's a concept that i don't understand he
would like start by boarding that's how we use kind of like our one-on-ones so he was a big
part of me learning the data science so i ended up doing six months i did a lot of learning i saw
what my teammates were doing i would like to view their projects um and eventually i got assigned my
own projects and i would learn and then i would apply and i think that's what made my knowledge
uh gave my knowledge more strength because i was learning and applying at the same time
i feel like in a lot of the online courses what happens is that you learn but you don't really
apply and like even the tutorials that then you'll see would learn and not apply it but i
think for me what helped is that i was learning i was applying at the same time and i was delivering
um so eventually ended up building up portfolio projects um and add that it was perfect timing
because it was the same time that amazon introduced their job family called data scientists
and this was uh i believe that was around 2018. my manager then um he took my portfolio he took
into the team the case for me that my my job family needs to be changed from a data
engineer to data scientist because that's what i'm doing and i'll have to say that he did fight
for me quite a bit because hr was kind of pushing back on the idea of me becoming a data scientist
because i don't have a phd um or i don't have um idea science degree but my manager fought for me
um and he kind of built the case saying that if she's already doing the work why do you
care about the degree why do you care about that stamp and that really really helped and eventually
me and along with two other teammates of mine we transitioned to data scientists so yeah i did i
spent like three more years in that team worked on a lot of cool projects got to learn a lot more
uh my focus area at that time was more working on the experimentation space so pretty much like
all the experiments and tests that were getting um getting tested on the amazon.com um
or like any existing features that would get modified would have to go through my team and
i have to work with like so many cool teams like the home page team the checkout team the prime
team the non-prime team amazon video team alexa team uh aws like i got exposure to pretty much um
a lot of the different teams that are supporting amazon's business and got to work with a lot of
data scientists um got to provide i eventually became the experimentation expert i would also
like give trainings to other people um who want to become experts and then um those people would go
and give training to other people so i kind of had like grandkids grandkids student basically
um so yeah kind of like my first few years working as a data scientist along the way i think i have
fallen more and more um i've fallen more and more um in love but not in love i think that's
a strong word i would say like data science gets me excited anything data related gets me excited
um now going back um if you like did having a business degree help me did having my
data engineering background help me 100 i feel like my business background and my data engineer
background makes me a very very strong candidate for a data scientist and i'm sure you probably
have heard that before like if a person doesn't know how to pull their own data or like do data
pipelines they are automatically at this advantage for a data scientist so i feel like that gave me a
leg up because i would know where to get the data from i would also know like how to talk to the
business people how to translate that technical language and turn it into a non-technical language
and then communicate with the stakeholders so that really really helped me um my networking
skills definitely play a big role which i i have to thank business school for for that so
yeah that was my journey in data science i hope this was useful i know i went on a tangent here
and there but uh hopefully this is helpful to you um i'll do probably another video in terms
of like what are some other avenues that i was considering for transitioning into data science
or what you can consider because i understand that everybody not everybody has an option to
transition to a different team within your company and then have that right mentor set
of mentors and access to projects um to be able to do that so i'll definitely share a little bit more
what are the other options that you can pursue to transition into the distance field
i hope this was helpful and if you liked the video please give it a thumbs up and
tell me in comments what else you would like to know about data science