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?