So far on the channel we've only talked about how amazing it is to be a data scientist
but today let's shift gears and talk about the five reasons why you should not become
a data scientist. I'm Samanvay, a data scientist based in Sydney, Australia.
The first reason why you should not become a data scientist if you only want to work on models.
As a data scientist you'll never be working just on models. You might be forgiven for thinking so
because model is usually the first thing we talk about. Often to the extent that we forget what
data science is really for. Data science at its core, it's all about solving business problems
and depending on the problem it this might or might not use fancy models. I would say
modelling is less than 10% to 20% of the job of a data scientist and the data scientists at
Google agree with me. The other tasks you do as a data scientist in no particular order include
dealing with stakeholders, developing a data product, designing A/B testing experiments to
validating your solution and doing the occasional data cleaning or data wrangling. You'll be greatly
mistaken if you choose to become a data scientist solely for the purpose of working on models and if
you're curious about what I do typically as a data scientist then be sure to check out this video.
Now the second reason why you should not become a data scientist is an obvious one and it's if
you hate coding. There's no denying that the job of data scientists requires a fair bit of
coding and it's okay if you're not that great at it just yet but if you have the enthusiasm and the
willingness to learn you'll definitely become a better programmer but it is an issue if you
hate it. Pretty much everything you do will require you to code to a certain extent and that
coding knowledge will also help you understand other coding related tools such as docker and git
and also allow you to learn other useful languages like Scala or Spark. Good coding practices is a
must as a data scientist. Think of coding as being the tool that data scientists use just
like a plumber uses a wrench and a painter uses their brush. And if you're looking to get better
at your python programming skills then check out this video I made recently. I truly believe that
anybody can learn coding as long as they're willing to put in the effort and they're willing
to learn and I honestly think that learning to code is a superpower in the century. Now the
third reason why you should not become a data scientist is if you like to be told what to
do. Inherently the problems you try to solve as a data scientist will be open-ended and ambiguous so
you really have to be a self-starter, resourceful and curious to be able to find solutions to these
problems because it'll involve you breaking the problem down into its smaller pieces and solving
each one accordingly and of course you can ask your colleagues for help but that's always not
going to be the case because you might be working on a completely new project that nobody else has
tackled so many times you'll be in a position where nobody really has answers for you so the
process really has to be curiosity driven and this brings me on to the fourth reason for not becoming
a data scientist. If you're enjoying the video so far then consider subscribing I make weekly videos
about demystifying data science. Let's get back to our fourth reason which is money. There's no
denying that the compensation for data scientists is pretty good but if that's the sole motivation
for pursuing data science then you'll end up being very miserable because the job of a data scientist
is far from easy. Many times you'll be doing some pretty unforgiving tasks and it's only if you've
got an intrinsic motivation other than money that you'll be able to survive in data science such as
learning from really smart colleague, working on very interesting problems, using your curiosity
to be a data detective and helping businesses thrive through the power of data science and due
to the concept of the hedonic treadmill you'll get used to that money very quickly. So it's
really all of the other drivers that I mentioned earlier that's going to keep you in data science
and help you thrive. The final reason why you should not become a data scientist is if you
hate working with people. Data science at the end of the day is a collaborative exercise .You'll be
working with internal and external stakeholders, your colleagues that are other data scientists,
machine learning engineers or software engineers. You definitely won't be like those coders that
stays up all night coding on their own through the night. Not that any of those exist anyway
as most tech jobs are very heavy on teamwork. So a large part of the role of a data scientist
is dealing with different people and another thing you'll be responsible for is acting as the bridge
between the business and the tech world which requires very strong communication skills and also
the ability to simplify complex concepts based on the audience you're speaking to. That's a wrap
for today. So if you enjoyed the video be sure to smash the like button and I'll see you next time.