All right, so some of you might know that I just quit my data science job at bank
the reason why I'm not seeing explicitly which company
It's in case I need to go begging back for my job, you know, and I don't want them to say that
Oh my god, what did you say this about a company?
We're not gonna take you back now before I go into why I quit my job
I kind of have to re-explain what my role was as a data scientist
and the reason why I have to react splain it is because
It's not as standardized as like software engineering which is I mean III know I explained in a lot of videos
but I'm just gonna do it again just so that you can have
the right context to understand why I quit so basically
this was my job title at this company and
Yeah, so you can read it
so in essence in my words
A data scientist is usually put into a product team and usually in the product team. There's a product manager
there are software engineers and there's a data scientist now, obviously there are other roles, you know, for example like UX researchers and
Like product specialists
Marketing people legal people and stuff like that, but I'm just gonna you know, simplify it and say ok
So there's software engineers and data scientists and product managers
So I'm not gonna explain it in a way where it's like, oh data scientists. They make models
They use like R and likes are for engineers, they build infrastructure and they use programming languages blah blah blah
I'm not gonna explain like that
I'm gonna explain it in a more fundamental way of what their roles actually are. So
Engineers they actually have the technical abilities to build the thing. We actually want to build product managers
They're basically the leaders are like the owners of the product. They decide what the product is going to do
And also what the product should be doing. Basically they have the vision and they're in charge of actually executing getting the shit done and
You know, they'll do whatever they need to do to actually ship a product in some ways
You could think of them as like mini CEOs of a product or a feature and then data scientists
we have the most time to think because we
Don't need to like build anything like for engineers and stuff like that
And we also don't need to focus on execute and talking to cross-functional partners all the time
So in some ways because we're able to think more than those two counterparts
We're basically like advisors are like consultants of like the product. We don't actually make the final decisions and calls
I mean obviously your opinions matter
but in in essence the the people who had the final say are kind of the product managers and also the engineers because
The engineers are going to build it so they could build whatever they want and then product managers
They're the ones
They're the ones that decide on the future of the product now because we have so much time to think our job is
To try to understand the product inside and out. We're suppose
Not I'm not saying all data scientists do that
but I think
That the fundamental role of a data scientist is to understand the product in and out better than anyone else
The reason is because like I said, you have more time to think you have more time in your hand
So basically we use data to try to understand exactly
what the product needs and where the product should go in terms of the product direction and
What we can do is we can tell our team exactly where we should prioritize and how we should do certain things
Why because we have so much time to think about it, you know, we don't need to build stuff
We don't need to execute on anything. So that's a role
We're always making sure that the team is working on the most important things
Currently, okay, I'll do one more analogy just because I like doing analogies. So imagine a youtube channel, right?
Engineers would be like video producers which is the people who actually know how to make videos because in the end if you don't have
A video you're not gonna have a video channel
so I think of Engineers like video producers and then product managers, I think of product managers as
The people who?
What it doesn't need to be multiple people
it could just be one person but basically the person who sends emails tries to look for sponsorships and
They think about okay, where should this channel go? Basically they do everything that's not related to videos
You know, we got Brandon we got sending emails making websites communicating with other youtubers. Basically just all the crap that
Video producers might not want to do so
I think those people are like the product and then we got a data science
The data scientists would be kind of like an an analyst of your YouTube channel
What analysis would do is they would all they always look at analytics to make sure that?
You know you get some insights to know what kind of videos to make next like for example
You look at the views and they say that okay
You know these things are kind of hot right now or this is kind of trending
And you look at comments - basically
You're like you're trying to understand your users the best way you can using data or anything. Actually, it doesn't even matter
It doesn't even need to be data. So basically
those are the fundamental rows basically a data scientist should figure out you know how to get more subscribers how to get more views and
Why are certain things working or are certain things not working?
So then give them insights give the product manager or like the video producer insights into like okay, which you make next
How should we you know like these strategies? Okay. I know that was kind of long just to explain
fundamentally, what a data scientist is
Fuck I need water
Okay, I'm too lazy to get water okay, but um basically the reason why I quit my data science job in essence
It's because I'm still exploring
so I guess what I'm trying to say is a lot of people are content with their first job out of college and
For my case. I think that
For the first years out of your college
It is totally okay to keep searching and try to understand yourself and try to understand what exactly
Is a right fit for your in terms of a job like I prioritize well, I might be wrong
I don't know but I prioritize long term like for example, if
you know, I just stuck of data scientists and
In the future. I realize I hate the job
then the cost of switching jobs is a lot higher later on if I was already five years or six years in so I do
think that sacrificing the first few years
Trying to discover what you actually want
It's definitely beneficial for your career. Hopefully, I don't know
We'll see so I'm not saying oh by the way, I'm switching to software engineering
I have a feeling that some people don't know but I'm not saying that software engineering is my
True calling or that this is the final job that I want. I don't know. I'm not sure I might be wrong
You know, I might not even last for like another year or two
But in the current state that I am right now
I feel that I don't want to do you know the analytics part like, you know?
The YouTube guy where he just looks at analytics. I kind of want to make videos
I want to be a video producer
So in this analogy, it means that I want to build things and I think that's currently what I want
at least what I think I want so that's why I'm gonna try out a software engineering now and
Yeah, cuz I thought that I was always a builder, you know, I do like some aspects of data scientists
But you know, I want to try to build stuff this time like I think at the core
My personality does fit more of a builder, you know, I do like building stuff. But yeah, so yeah
So those are the arguments of me wanting to become a software engineer
So I'm gonna talk about some things about why I don't want to be a data scientist anymore
So at least at my company or my old company the way you get
Evaluated no matter what role you have is how much impact you have?
And basically what impact means is if you did you have like a positive contribution to the company
So even if you worked your ass off or you did, you know, you do a lot of smart intelligent things
But it doesn't have any positive impact to a company or like it doesn't really change anything
Then you still might get fired after a while. So as a data scientist using the scope that I talked about like the fundamental ROS
basically
how a data scientist can have impact in a company like that is by
Make like being like influencing the product. This is
influencing the product direction
so for a data scientist using that scope of like fundamental ROS a
Data scientists how they can have impact is by you know
Making analysis or something such that it leads into
actionable
Insight meaning that people will use that insight and then they'll take action to towards it and then it will benefit the company
So that's impact. All right, so I have a few examples. I'm just gonna read it out loud because I I can't remember them
So basically in a simple way if your analysis convey the engineers to build something and our metrics went up
That's impact
Also, if your analysis convinced the PM and the team to put a new feature a or a project on the roadmap
That's impact
If you create an amazing
Prediction algorithm to predict whether a user watched a video with alone in their apartment or with friends
But the team didn't decide to implement it because they don't think it's useful that is not impact
if you found that Korea is a growing market for live videos and you have tons of evidence that
Adding a donation button can make your company dominant in the live video market in in Korea
But even with their sound evidence you cannot convince your product team to focus on Korea. That is not impact
So as you can see
it's not always a hundred percent fair because for some team it might be easier than another and
There's a lot of factor that plays into the success of a data scientist and some of them are out of your control
And that was one thing that I found a little bit harder to cope with
Now I've worked with teams where it was really really easy to find opportunities and then you show those
Opportunities to them and then they're super excited and they'll do it, you know, and that's a lot of impact
but I've also worked for teams that
Move a lot
slower against a more friction and basically, you know
you don't have as much credibility to them and
And it's a lot more difficult to convince them to do what you want to do. So that's why it's a little bit harder
So and basically if you have no influence, you don't have impact as a data scientist now
Sometimes you might be lucky that your work is so good that your work speaks for itself, right?
But the reality is that in life that's not always the case. Sometimes you just have to be influential
Basically, you have to have the skills to influence your peers let your engineering manager the product manager
you have to get them in the same team as you or you have to basically or
Basically, you have to kind of convince them that your ideas are good and that they should implement it. But that's the thing
It doesn't always happen and sometimes you gotta be pretty good at like the office politics or like
you know stuff that or more like soft skills ish and
I believe those were the skills I lacked or at least that's why I thought before and which made me kind of like yeah
Like believe it or not. I'm actually
kind of like a work introvert so
I'm also like still very inexperienced in in in understanding like the work
Dynamics and also like some office politics and stuff like that
I'm still quite new. So I mean I did get better but at the time
that was what made me want to switch to software engineering because I felt like I wasn't ready to be a product leader on my
Team, I didn't feel like I had the maturity to make and influence decisions on my team
I didn't have the confidence in myself nor my work and that
Stressed me out. Yeah, that stressed me out now. Don't get me wrong
there's a lot of
aspects of data science that I
Enjoy and that I like and that I still like and I do hope that when I work as a suite that I could use
some of the things that I've learned and
and use it as my advantage but basically how I think about it like my philosophy is that your goal should be like
Oh, I should be really I should be a really good data scientist, or I should be a really good software engineer
You should be the ultimate worker
Okay, that sounds kind of weird
But basically what I'm trying to say is you want to be the guy who can solve everything with anything, right?
Like if there's a problem
You're the guide to solve it
No matter if it's a technical problem a business problem or like analytics problem and stuff like that
you want to be the guy that people can depend on and that's the person that I'm trying to be and
For now the skills. I want to work on or you know building skills like a software engineer
So yeah, I mean, I haven't done that in ages. I kind of miss it. Okay
So now what you know, what am I doing now? Well, I am unemployed
So basically what I do is every day, I just sit on my ass and I work on interview problems
I do a couple of questions on alcoholics per die. Oh just so that I can refresh my memory on these coding interviews. Yeah
It's a good website. I highly recommend it
Yeah, you should check it out. If you're if you're interviewing also, what else have I been doing?
Yeah, so, you know because I have so much time in my hand
I've been going to blind a lot blind. Is this like Anonymous?
Forum app that you can check you could check like gossip
so basically when I worked at like my company X
what I could have done is I could have gone to
Blind and see what other people were talking about that also worked at company X so a basic a lots of gossip
But I also use it for non gossip and there's a lot of stuff that you can read about in like normal topics
We're just a bunch of people from Silicon Valley
They just talk about random stuff and most of the time to talk about, you know
switching company
interviewing at your TCC
Total compensation how much they make it's a good way for me to get a feel of what the market is like right now
So I use it a lot
Almost obsessively a lot of times I check like okay, you know
You know company X interview process to kind of get a feel of like how they interview you. So that's what I do
I mean you guys should totally check it out. It's pretty cool
You know lots of lots of anonymous talks there
yeah, so basically, um, you know, I mean I get a lot of questions sometimes from people saying like oh,
How should I do X or where what should I do to find X Y or whatever. Oh wait, my camera's almost on
Yeah, so pretty much like I get a lot of questions where sometimes I don't even know the answer
But how do I get the answers, you know, I go to Google I go to you know algo expert to learn some stuff
I use blind to understand how the interview process or like I use a lot of these websites
So I feel like you know instead of me answering all the questions for you guys
I should just give you the tools to answer these questions, right? So there's this quote. You know what they say
Give a man a fish and you feed him for a day
Teach a man how to use blind and they will get into a career and buy organic fish from Whole Foods
for a lifetime
Alright, that's all I have to say for today. Thanks for watching
peace
Forgot that feeling the Sun in my face, it's our well needed