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Day in the Life of a Data Scientist in San Francisco

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Day in the Life of a Data Scientist in San Francisco

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60 segments

0:03

I didn't announce this on

0:06

the board some of the ship criteria.

0:45

It's good.

0:47

You look like a young Smurf.

0:48

like Romeo and Juliet.

1:06

My first task of the day was wrapping up

1:08

an AB test. An AB test includes showing

1:10

two versions of a feature or experience

1:12

to different users and analyzing which

1:14

performs better. My experiment just

1:16

ended, so I'm examining if there's a

1:17

statistically significant difference in

1:19

metrics, summarizing the results, and

1:21

recommending which version we should

1:23

ship.

1:29

Hey, how's it going? Next, I'm hosting a

1:31

post-experiment sync with the PM and

1:33

engineer to review key takeaways from

1:35

the data and align on whether to ship,

1:37

unship, or reiterate the feature based

1:39

on the experiment results. Though much

1:41

of my role is allocated to analyzing

1:43

data, another crucial aspect is

1:45

communicating the insights to

1:46

stakeholders, helping them land on the

1:48

best decisions for the product.

2:11

How's it going, Andrea?

2:13

Hey, Jen. What's up?

2:14

Camera. Are you going to be famous?

2:15

Yeah. Apart from experiments, I build

2:18

more extensive analyses to answer

2:19

questions like, "How did user behavior

2:21

change after launching a feature?" or

2:23

"How can we improve this user flow?" We

2:26

investigate this using data with the aim

2:27

of flipping learnings into

2:29

recommendations. Here, I'm sharing my

2:31

initial findings with a fellow data

2:32

scientist to get early feedback on my

2:34

current project.

2:50

For the rest of the day, I'm working on

2:51

a dashboard for my team's upcoming

2:53

feature launch. This dashboard will

2:55

track success metrics so my team can

2:57

monitor usage of the feature during and

2:59

post launch. My tasks involve

3:01

brainstorming the most useful metrics,

3:02

querying those metrics, and designing

3:04

the dashboard so it's easy to read for

3:06

everyone.

3:22

I love you.

3:30

Hey, since I saw you last, it's been

3:33

It's been It's been 9 months.

3:37

Sorry, but here's what you missed. I got

3:39

this couch, and this coffee table, and

3:41

this espresso machine, and this TV,

3:43

which is still on top of this guy, but

3:45

I'm going to change that today, okay?

4:11

And now my setup is complete and my

4:14

lease is almost over.

Interactive Summary

The video provides a brief look into the daily responsibilities of a data scientist, focusing on analyzing AB tests, collaborating with product teams to make data-driven decisions, and building dashboards to monitor feature performance.

Suggested questions

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