Name: 私がFANG（Facebook Amazon Netflix Google）でデータサイエンスの仕事を辞めた理由 (Why I left my Data Science Job at FANG (Facebook Amazon Netflix Google))
Uploaded: 2021-01-14T10:19:48.000Z
Duration: 15 min 17 s
Description: VoiceTubeの動画で発音を聞きながら英語表現を覚えよう！学べる英語：

過去形

All right, so some of you might know that I just quit my data science job at bank

現在進行形

the reason why I'm not seeing explicitly which company

to 不定詞

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

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

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 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

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 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

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

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

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

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

Okay, I'm too lazy to get water okay, but um basically the reason why I quit my data science job in essence

so I guess what I'm trying to say is a lot of people are content with their first job out of college and

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

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

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

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私がFANG（Facebook Amazon Netflix Google）でデータサイエンスの仕事を辞めた理由 (Why I left my Data Science Job at FANG (Facebook Amazon Netflix Google))

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