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Data Scientist Vlog | vancouver work trip, 9-5 routine, post grad life

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Data Scientist Vlog | vancouver work trip, 9-5 routine, post grad life

Transcript

102 segments

0:02

[Music]

0:07

That was good. That was really good. I

0:09

have no meeting day, which means it's

0:11

the best day of all time.

0:13

[Music]

0:21

[Music]

0:30

So, I'm literally in Vancouver right

0:33

now, which is so crazy. It's also my

0:36

first time in Vancouver or like Canada

0:38

in general. And also, this is my first

0:40

work trip. It's just mainly to get to

0:42

know the team because my team that I'm

0:44

supporting is currently based in

0:45

Vancouver. So, here's the bed and the

0:48

desk and a little reading nook area. And

0:50

then here's the bathroom with the

0:51

bathtub and the shower. And look,

0:53

there's a literal Dyson. Like, I've

0:55

never seen that in a hotel before.

0:58

[Music]

1:05

Outside of meetings, most of today's

1:07

experiment work, checking that treatment

1:09

and control groups are balanced, and

1:11

digging into any issues that come up.

1:13

One test just finished, so I'm writing a

1:16

report that breaks down the results and

1:18

outlines key next steps for follow-up

1:20

testing.

1:22

Y

1:29

[Music]

1:35

so hot

1:39

[Music]

1:41

to the stage before.

1:45

>> Oh my god. What's going on?

1:49

Bring it down.

1:56

[Music]

2:02

Yeah, you learn that. A lot of

2:09

[Music]

2:26

It's too late. It's too late.

2:30

>> Yay.

2:31

>> Yay.

2:35

[Music]

2:40

>> A

2:40

>> Wow.

2:42

>> Oh. Oh.

2:46

Oh wow.

2:49

Okay.

2:51

[Music]

3:04

I'm back in San Francisco. I honestly

3:07

wanted to vlog more of Vancouver, but it

3:11

was such a short trip and I didn't

3:13

really have time. Vancouver was so nice.

3:16

There's a lot of stuff to do and there's

3:18

like really, really good food. I'm

3:20

actually so glad I was able to finally

3:23

see them in person and not over Zoom all

3:25

the time. So, today is going to be a

3:27

kind of chill work day. I have no

3:29

meetings, which means it's the best day

3:32

of all time. And that means I have some

3:34

time today to finish some tasks that I

3:36

have not had time to finish. Finally,

3:40

today I'm opportunity sizing for a

3:42

potential AB test. A big part of product

3:44

data science is helping the team

3:46

identify the highest impact

3:48

opportunities to improve the product,

3:50

which means digging into the data,

3:52

checking user traffic, and estimating

3:54

how much revenue we could generate from

3:55

the new feature.

3:58

[Music]

4:15

Heat. Heat.

4:19

[Music]

4:29

[Music]

4:35

Hi. I'm back from the office. So, I'm

4:37

thinking I'm like going to go for a run.

4:39

Yeah. Yeah. I've been trying to get more

4:42

into running. I used to only do the

4:44

12330 at the gym, like on the treadmill.

4:46

I got kind of bored. Like I kind of

4:48

needed to touch grass and a change of

4:50

scenery. I actually saw this meme where

4:52

people after they graduate college, they

4:54

get sorted into one of four houses like

4:57

Hogwarts. And I'm like trying to get

4:59

into running. Like I'm trying to get

5:00

into the running house, but like yeah,

5:02

I'm like bottom of the class, but I'm

5:04

like trying. I'm like trying. Anyways,

5:07

um come run with me. Oh,

5:11

[Music]

5:30

heat, heat.

5:34

[Music]

5:52

You don't have to worry.

5:53

>> So, I just started watching Mr. Robot

5:56

and so far I am super surprised by how

5:59

hooked I got on that show. Like so fast.

6:02

Anyways, it's all that I had for you

6:04

today and I shall see you in the next

6:06

one. Bye.

6:07

[Music]

Interactive Summary

This video follows a product data scientist through a work trip to Vancouver, offering insights into her professional responsibilities such as running AB tests and performing opportunity sizing. Upon returning to San Francisco, she discusses balancing work tasks with personal hobbies like running and watching TV series.

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