Hi friends welcome back to another youtube video in today's video we're going to talk about
my struggle with finding a job as a data scientist yes it may look like from my profile that i had it
easy but honestly that [ __ ] was hard excuse my language but honestly that was hard like it was
not easy and i specifically struggled with finding job as a data scientist in the data
science domain and i'm going to talk about exactly what are those things that i found it difficult
so before we jump into the video make sure to give this video a thumbs up and subscribe to my channel
if you want to hear more about data science tech lifestyle and everything else in between
so a little bit of back story in terms of like where i was coming from when i started looking
for a job as a data scientist so in my previous company i worked there as a data scientist for
about three years that's when i decided that i need to leave and i need to like look for
my next opportunity and do something different so i started searching for jobs like typically
how i would go previously before i was a data scientist i would go and apply for jobs but
pretty much right so there are three things that i learned that are pretty much
i struggle with quite a bit number one are the job titles such as the title data scientist
means different to each company which means a data scientist at company x does not translate
to data scientists at company y and that made my job search much much harder because
now what i had to do is i actually had to go read the job scripts and look for like
google open jobs for data scientists or go to whatever platform that i was using right
and look for data science's job and then i had to like read in between the lines to understand
like okay is this a data scientist job is this applied scientist job is this a data analyst job
so one simple example would be for example a data scientist at facebook does not equal to a data
scientist at amazon or data scientist at google but a person who has not been in the industry or
who are new new to the industry they would have no idea they would apply for the job and let's say if
they get the interview call they're going to go into interview and they're going to fail because
the skills do not match even though the titles specifically match so i struggled with that
quite a bit and i had to put in extra work to understand read all the job decisions one by one
not pay attention to the title although i would have to like use the keyword to find the job so
which is like it's possible that i probably missed some opportunities because if i was looking for
the title and the title does not match tie up to the job descriptions and does not tie up to
my skills that means like i'm probably going to like miss some opportunities along the way
in that search in that whole pipeline so that i specifically found like super super frustrating
because one thing i wish like that would happen down the road is like i hope like the data science
field gets a bit more standardized compared to other job families such as software developer
jobs or web developer jobs and things like that the second thing i struggled with was again the
going back to the job description and allowing matching the skills is the interview process
similar to the job titles and descriptions the interview process was not standardized the problem
does not change right i go to the interview like in the interviews i struggled with the same thing
where i would be invited to interview for a data scientist role right that's what i applied for but
when i go there the whole interview is pretty much for a data analyst and that would then give me an
idea okay like yeah that even though like the job description was hiding for a data scientist a full
stack data scientist generalist but they were actually looking for a data analyst which again
like reminded me that if they are interviewing like this that every person is hired based on this
that means like the people that i'm going to be surrounded with are primarily are going to be the
data analyst or business analyst set of skills nothing wrong with that but it just gives me an
idea so that was also frustrating part because i would put in a lot of effort preparing for the
interview coordinating the interview applying for the job and then going there interviewing sitting
there for hours doing five interview loops just to figure out that this actually is not the role that
was listed in the job subscription and it's pretty much something else that i am not interested in
so that happened a lot um and that was the most frustrating part because in the initial search
process i could like look at the job description i can go back and forth and i can try to figure
out in my own time to like what does it actually mean but when i'm already ahead in the pipeline
when i have already put in the work prepared for the interview and actually done the loop with sat
in a room for five long hours talking to five different people going through like those
rigorous questions and just to end up to realize that it's actually not what was portrayed to me
initially so again like it all goes back to like standardization that made it uh pretty difficult
some interviews end up being very very like computer sciencey some interviews end up being
very data analyst or business and analysty which made it like super super difficult to kind of like
end up somewhere and that uh increased my because i was interview i would interview and then i would
realize like okay this is not what i want to do or this is what's not what is sold to me and then i'd
be like okay i don't want to do this like and then i go back to square bun and then start doing that
thing all over again so that was the second thing the interview process again is not standardized
and i hope something happens in the industry where the job descriptions the job titles and the
interview process eventually gets standardized to some extent not like i know it's never it's
never going to be perfect but to some extent like somebody needs to provide some guidelines
to all these companies at once so they're not like each figuring out like labeling their own
things next to a job description and doing a very random interview questions and rigor my
last and third struggled with the data science job family was there were not many open roles
even though like we say like the data scientist is the new thing it's the the sexiest job of 21st
century there were not many data scientists roles in be looking for jobs in an entire dev
team which is like filled up with like probably 10 people like would be software developers pm
software developer manager they would need one data scientist right so an entire team
has only one role open for a data scientist so let's say if a company in a company there are
10 different teams they are hiding only 10 data scientists but they're probably hiring
30 software developers to fill those teams so which makes it very very difficult
right because they're not a lot of openings and the openings that there are given that there is
so much hype around the job family there are so many people in the market right which makes it
very very competitive that means you have to be excellent in your interview performance
and again like going into the interview you don't know what you're going to end up in
so sometimes it's a bit of luck too right like ending up in the right interview loop with asking
with the right set of questions that align with your skills and align with your preparation so
yeah like those are my three things like the job titles are not standardized the interview process
is not standardized and third they're not enough jobs for the people the number of people that are
in the market so a lot of supply demand supply demand issue i believe i know this i did not
give you any tips but i honestly wanted to every video cannot be about tips i just wanted to share
what are some of my common frustrations which as an individual i don't think i can solve i think
there needs to be something bigger that needs to happen industry-wide at the industry level for
this problem to solve so and again like nothing is perfect i'm not saying like other raw families
are perfect but i think there's definitely doom for improvement in the data science
dot family for sure so let me know in the comments what were some of your struggles when you were
interviewing for the data scientist role or any family in the under the data science umbrella
i would love to know like what are some of your common frustrations did you share any of mine
the the three things that i mentioned any of the things that i shared did you did those
resonate with you specifically when it came to your job search let me know in comments with
that thank you so much for watching and i will see you in the next video have a beautiful day