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  • All right.

  • Welcome to another interview, guys.

  • Who got Cameron today?

  • You know, your least favorite character in the start of Siri's.

  • They talk five character in the start of serious.

  • Yeah.

  • I mean, thanks for coming.

  • You were definitely the cheapest toe get here.

  • So think you're paying everyone else all right?

  • I don't pay a buck.

  • All right, That's good.

  • Start first things first for people who know who washed the start.

  • Siri's.

  • Well, first of all, if you don't watch it, you should watch it right now.

  • Okay, There we go.

  • Now, the thing about Cameron in startup Siri's is that he's a very hungry say, a romantic character.

  • He's very passionate and stuff like that.

  • So how are you in real life is, like, the only know you Cameron as a character, but they don't know you as you.

  • Well, they say life imitates art.

  • I think romantics a nice term desperate is probably a better term for the 3% of viewers who are women.

  • I am single, you know, um, I think at the beginning, I didn't really know what my character was going to be on the start of Siri's, and then I just came to realize like my acting's not great, but I could be myself.

  • I think you're acting is great, unless that's just yourself.

  • I am a loveable dork and really right.

  • Like when I was struggling doing push ups, I was actually starting to put.

  • That wasn't acting.

  • That was reality.

  • I did tell you to do like a shit ton, but because we kept, we kept like we're taking the same thing.

  • I was exhausted by the end of the heavy breaths.

  • Those those were real.

  • There's a little bit of reality.

  • There's a little bit of a joke.

  • I think it's me to the extreme.

  • So so are you a programmer?

  • Are something else in the start?

  • Siri's your programmer.

  • I've written how little world in a few different languages impressed, But no, I'm not a program data scientist.

  • So your data scientist, it's nice.

  • So let's talk about career now.

  • So as a data scientist, first of all, where did you work?

  • Uh, graduated out of UC Berkeley on, and then I worked for tender for a couple of years, and now I am working on unnamed large tech company in the bay.

  • Well, sec, I wonder what that is.

  • No idea, Dio.

  • They call it like head pages.

  • I think of that.

  • I wonder I wonder what it is.

  • You know the way so tender was your first job?

  • Yeah, that is crazy.

  • Interesting.

  • So you might know a lot about relationships or at least dating.

  • I'm one of those people who joined tinder cause I didn't know how to relationships.

  • I think, like maybe I've learned So did you learn anything?

  • Oh, yeah.

  • I learned a lot.

  • I went on How many dates wise?

  • My first year.

  • A tender.

  • I went on one date.

  • It was bad.

  • Well, maybe you were just very selective, right?

  • No, I was right.

  • It's, like, constantly get along matches, though.

  • No, no, no, no.

  • I had to put in work to get matches, But, you know, the first year was closer, Roughy.

  • And then eventually I started figuring out what to do and everything I'm like.

  • No, I was going on dates one or two dates a week by like, my second year a tender just cause I figured out what todo wow, That's actually a lot one or two days a week.

  • I'm a first date machine second day.

  • It's not so much you never once done kind of deal.

  • I'm gonna ask you more questions about that later because I want some tips also.

  • Yeah.

  • So you went to Berkeley and then wait, What did your study such?

  • That you went to data.

  • So how do you even know about data signs?

  • Good question.

  • Um, so I was bioengineer numerically.

  • I was pre med on.

  • Then I took organic chemistry and realized they hated it.

  • So you're supposed to be a doctor?

  • Yeah.

  • Your parents thought you were gonna be adult.

  • Parents are both doctors.

  • They wanted me to be a doctor.

  • He'd sold you yet?

  • Uh, a little bit.

  • They made me take the cat when I Really Yeah.

  • They didn't make me study.

  • I did not do well on it, but they made me take it because they wanted me to change my mind.

  • They were hoping, you know that the change in their heart of hearts the TV I have to do is eight hours with so much fun.

  • But I gotta do this more.

  • I got like, Caribbean med school scores.

  • What does that mean?

  • So, like Kat, you got to get like, 10 points above the average to get into, like, a good U S.

  • Med school, huh?

  • I got four points above the average, which, just like you can get into a Caribbean med school is where, like, people go if they don't get into any of US men.

  • Schools hang out there for two years.

  • I did premed.

  • I graduated premed, But I knew at that point I didn't want to do do bio anymore.

  • I want to do some mixture of stats and psychology, so I blood Ph.

  • D is in game theory on.

  • I haven't taken a single e con class in my life.

  • And so I got rejected from every single PhD that I applied to, and so I I panicked a bit applied to 115 jobs out of undergrad on.

  • Then it was mixture of lake analytics, product management's and then you ex research in the Analects.

  • Once we're the only ones that really call me back because I had the math background for it.

  • So then I went into analytics a tender.

  • You were doing biomedical engineering.

  • Yeah, and, uh, and there were a lot of math and that I guess Yeah.

  • I mean, it's like a lot of engineering classes I like.

  • I like stats.

  • So I did a lot of stats class on the side and everything, like the bio in itself was enough to handle any of the math that you do is a data scientist.

  • Yeah, that makes sense.

  • Because I was wondering, with that degree today, even like, look at you because I feel like it would feel like, I guess, No, my team.

  • There's a lot of people who are late by on physics Peach to use like, yeah, my data science teams.

  • There's like a lot of people who came from, like a bio engineering background, actually more who do that, then come from like a stats, background or a math background.

  • And then when you start your first shot, but tender, did you enjoy it or did you not like, Why'd you switch?

  • I liked it, but I was working out in Texas.

  • Texas is one of those places.

  • Were like, If you have a family, it's nice.

  • It's great place.

  • Public golden retriever, two kids, white picket fence.

  • But like a 22 year old, you can only eat so much barbecue on, like I was putting on weight.

  • And I didn't really have any friends out there because I've never lived out there.

  • It always lived in California, and so, like, it just is boring.

  • So I tried to move back to the day, and when I did, I was recruited.

  • You could get really huge houses there is right.

  • She Did you get a nice house, like, $200,000 or so?

  • You should all move to Texas before it rises up again.

  • I mean, a lot of companies are going to Austin at this point.

  • Okay, well, I guess the price is gonna rise that it's going to It sucks.

  • So, did you study for your data science interviews?

  • I spent a week Marnix equal, like E did I think w three schools.

  • I just picked it up super quickly.

  • Also learned a lot from brilliant dot or GE.

  • That's be our sponsor.

  • This we're not gonna give them free sponsorship about that.

  • To get the data science interview, you need sequel, and then you need either are or Python.

  • And honestly, that's about it.

  • Like when I interviewed for analyst positions, like on the other end of the interviewer.

  • I kept on seeing resumes that were just, like, packed with every programming language possible and, like I usually trash them because the reality is that, like all these people have the exact same resume, like it's literally template ID.

  • Not like Doc, exactly.

  • Word for word, but, like, objectively the same.

  • And then when I see 100 of those, I don't know which 100 to pick.

  • So I don't think any of them the reason being like I look for people who have some distinct interest in the field, and that gives me a better signal like there's a reason they're applying this job instead of just slamming their resume out everywhere.

  • Sounds a little bit like dating.

  • It does sound a little bit like because, you know, my profile just generic.

  • So I complied most.

  • Do you have a can pick up line?

  • No, I don't.

  • Actually, I just say, Hey, you say hey and that works.

  • No, you're looking.

  • I mean, that's the thing.

  • Like if they're girls, I don't care about that.

  • I say, Hey, because if they say hey back and talk to me, they must really like me.

  • So I'd be down if someone's reads like, really into me, right?

  • But if it's someone that I think she's so hot early, which is so interesting, then I'll take more like I'll take the time to like like a profile try, think of a funny line and then do it.

  • How many responses do you get when you say Hey?

  • No.

  • When I tell you, yeah.

  • Oh, yeah, I went out of 10.

  • That's actually pretty good.

  • Really, That's actually not bad.

  • So I mean, I don't get along matches either, right?

  • So you're saying as if you have 10 matches Do you think is in complete sampling a small numbers, half a response on five.

  • So what did you learn about dating when you worked at Tender Man so much?

  • I'm gonna try not talking about the math part first, because like, I think there's a lot of cool math and there's a lot of the optimization, like what I learned more about was kind of the mindset of dating off.

  • And by that I mean, like, you can really go into dating with two different mindsets.

  • Well, first off, you could just not date, and I know a lot of people do that and like they're happy doing that.

  • But they also want to get married, and they just don't know when that's going toe switch.