The Data Scientist Show | Daliana Liu

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Watch the video of this episode: https://youtu.be/ldXGeOjGkx4

Memorable Quotes from the Episode:

[00:37:10] "Whatever we can do to actually, like, connect to our fellow man and woman is really, really important. And exercise and activity is a big way to do that. And the community serves our mental health. Whether you're an introvert or an extrovert, it doesn't really matter. Being around people serves you and allows you to feel like you're part of something like a belonging, right? So I think in all those ways, activity and exercise is huge for individuals who are just really trying to establish a baseline of mental health."

Highlights of the show:

[00:00:09] Guest Introduction

[00:02:05] Where you grew up and what it was like there?

[00:04:19] When you were in high school, what did you think your future would look like?

[00:07:41] How did you gravitate towards math having this interest that seemed a bit like honestly, like artsy kind of interest. Did you see any kind of art in mathematics? Is that what drew you to it? What was that pool?

[00:12:05] How is writing been an important element of success in your career?

[00:15:58 How do you suggest people get better at writing? Is it just going through, like a business writing class, one of those free business writing classes? How did you get developed that skill?

[00:20:49] What are some other critical elements to success for someone's career as a data scientist that don't get taught in school?

[00:24:34] How did you learn different skills?

[00:27:10] I'm wondering if a little bit in there is that feeling of imposter syndrome, a feeling of not wanting to ask a question because you don't want to be perceived as not knowing something like, oh, you're supposed to be a data scientist. Don't you know how to do this? Do you notice this happening a lot with with data scientist of any career level?

[00:30:53] Let's talk about how your day to day work as a data scientist is. How is this different from what you expected it to be when you were an aspiring data scientist?

[00:35:23] What what do most data scientists do wrong when it comes to their career development?

[00:38:35] Where would you draw the line between a data analyst and a data scientist? Can you point to one skill and be like, oh, right there, that's it. If only you knew this one thing, you'd be a data scientist. Does it work like that? What are your thoughts on that?

[00:44:09] What are your thoughts on why people are giving you so much pushback around that particular thing?

[00:52:24] How do you try to ensure that you're providing as fresh a perspective as possible with the content that you create?

[00:53:33] What are your thoughts on what it means to be a data science influencer?

[00:55:19] Let get into your podcast "the data scientist show". Talk to us about that. How did that idea come into your mind that you want to start a podcast? Who should listen to this podcast? Do you have to be experienced in the game to listen to it? Or is this a broad spectrum of data scientists.

[01:00:07-01:00:15] Let's talk about your experience being a woman in tech and a woman in data.If you have any advice or words of encouragement for the women in our audience who are breaking into or currently in our data world?

[01:06:05] What can we do to foster the inclusion of women in data science and AI?

[01:05:07] It is 100 years in the future. What do you want to be remembered for?

Random Round

[01:07:12] In your opinion, what do most people think within the first few seconds of meeting you for the first time?

[01:07:41] You do like journaling in the morning or anything like that?

[01:07:57] What are you currently reading?

[01:08:42] Can you share just a couple of tips on how not to feel bad not finishing a book?

[01:10:21] Pirates are ninjas?

[01:10:31] Mountains or ocean?

[01:10:38] If you were a vegetable, what vegetable would you be?

[01:10:48] If you could live in a book, TV show or movie, what would it be?

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