224: This Recruiter Became a Data Analyst DESPITE No Experience

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And then I just cried, you know?

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I was, like, handling, like, 12

rejections a day for, like, a month,

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and then I changed it and it got better.

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So I think self-taught is a fallacy.

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The role that I applied for was

nothing to do with this job title.

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Okay.

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'Cause you only need one

impression to get the job.

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You need to say yes to jobs

that you're not gonna love them.

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You were able to transform your

career from kind of this call

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center HR career into this data

and AI career in about a year.

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I wasn't expecting that at all.

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Hey, guys.

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It's Avery, and that guy you just heard

from is one of my students, George Lopez.

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And a year ago, he was literally

answering phones in a call center,

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getting rejected from data jobs,

like, over a dozen times a day.

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Ready to quit, absolutely miserable.

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And today he works for an AI and

data team for a US company living

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in Mexico, and the job he landed

wasn't even one that he applied for.

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In this episode, he breaks down

exactly what he changed on his resume

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to start getting interviews, why

he thinks self-taught data analysts

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is a fallacy, and how he turned

utter rejection into an offer.

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If you're trying to get into

data, this is a great episode to

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listen to to get the playbook.

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Let's go ahead and get into it.

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All right, George.

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So you were able to transform your

career from kind of this call center

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HR career into this data and AI

career in about a year through the

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data analytics accelerator program

without having, like, a real a- IT

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degree or previous IT experience.

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Walk me through your whole

journey in this episode.

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Let me know, like, how you got from, from

A to B and how other people can do it.

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Let's start with, like, you

know, your first job li- like

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you were actually working at.

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You were working in call centers.

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Tell me what that was like and

then how you ended up in HR.

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Yeah.

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So I worked for all American

companies since I'm 18.

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Got my first job at 18 working

for MetroPCS customer service.

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It sucked, just being honest.

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Um, then I moved to AT&T tech support,

um, car rentals with Avis and Budget,

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and then I did a little bit of

sales, um, sale call center work.

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Then I did, um, collections for

a Long Beach company, um, more in

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the finance side of the industry,

but still kind of call center.

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After that, I started as a recruiter for a

call center, of course, for about a year.

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After that, I was promoted

to HR, same company.

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Um, and couple months later, I

landed a, a remote job, still

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HR, but for a US company.

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Um, and I learned a lot in that job.

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I worked there for almost four years.

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Um, and part of that is that, you

know, I started as an MSP, which

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is a managed service provider.

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Then I transitioned to a billing analyst

position, of course, which, um, we

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can talk a little bit more about that.

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Um, the course really helped me out

because I really sucked at Excel.

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And that's, like, my main

expertise right now Very cool.

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So you went from, yeah, I don't

think anyone would necessarily say

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that call centers are super fun.

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So you went from this, this sucky

job to you, you landed this billing

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analyst role, which is your first

step into the data analyst world.

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Um, you were there for a little bit,

and then most recently, as of recording,

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you just started this new job, which

is this, this project coordinator role

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with this generative AI operations team,

um, that, you know, you just started

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about, uh, which is really exciting.

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So like you're in the data and AI space,

you know, out of nowhere overnight.

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It really wasn't that, that

way, and we'll talk about that.

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It took a lot of effort on, on your

end, and it took about, you know, nine

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months-ish to a year of actually like

putting in the work to, to get there.

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Uh, we should also mention that

you're, you live in Baja, California

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in Mexico, and you've been working,

uh, these, these two data jobs are with

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American companies, with US companies.

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So, uh, that's, that's really impressive.

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I guess at like what point did you

decide that you were interested

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in data and AI and analytics?

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Because you, you really

had this HR career.

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You were a recruiter.

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Uh, at what point were you like,

"Oh, I wanna be a data analyst"?

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Because at work, I was the

go-to person for the system, for

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our vendor management system.

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Uh, we did a lot of reports.

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Uh, we have something called xAG,

which is built in with Power BI.

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That was like my first interactions

b- beyond, you know, downloading a

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report and deleting columns, applying

filters and whatnot in Excel.

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Um, that helped me out because I

automated the process by just using

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the system as data that I cre- I

created, but like scheduled reports

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with sp- specific filters that will

be sent, um, automatically via email

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to managers or the client, you know.

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Let's say first of every month you will

have a negative turnover r- report with

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specific filters, which will be the

first day of the previous month, and the

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last day of the previous month will be

sent on the first day of every month so

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that it's a monthly report of turnover.

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So I was playing with the system.

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I was like, "Huh, this is interesting,

you know, how we can project what's

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going on, the patterns, what it means.

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What can we do about it?"

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Because at ease, you know, at

first glance, you don't really know

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what's going on until you download

a report and start scratching.

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Hmm.

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Very cool.

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I think a lot of people can

probably relate to that.

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They're like, they're in their,

their career, they're doing this job,

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and they're like the more organized

person, the more analytical person,

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the more systems person doing the work.

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And it's like, "Oh, I actually really

like this, and I'm kind of good at it."

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So that led you to, to data analytics.

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You're like, "I wanna pursue,

you know, becoming a data

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analyst, um, in, in my career."

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And eventually, you, you found me.

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Um, was it via YouTube, or was

it via the podcast or LinkedIn?

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Do you remember even?

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It was YouTube at first.

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So it was because I wanted to enroll.

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Why I technically enrolled on the

course were Google data analytics.

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Um, I started it, like, af-

after, like, an hour I was

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like, "What the heck is this?

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This is just multiple choice questions."

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You know?

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I wasn't learning, I'm

sorry for my French, shit.

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I wasn't learning anything, you know?

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Um, and I was like, "What

else can, can I see?"

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You know, I was like, "Wait."

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So I, I Googled is a Google, um, course,

like, worth it, and then you popped up.

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Okay.

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Yeah, I definitely have done,

uh, an episode or two about the

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Google data analytics certificate.

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Uh, which I basically say the same thing.

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I say, "If you want a really

high level overview of

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analytics with people asking…"

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Not even people, just a computer asking

you multiple choice questions that

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don't actually get you much hands-on

experience, then sure, it's for you.

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I think in that episode I actually

count how many different sequel

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queries you write, and it's, like,

20 different sequel queries that

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you write in a six-month period.

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And it's like Guys, come on.

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We can do faster.

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We can do more than 20

SQL queries in six months.

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We can do, you know, 40

SQL queries in six weeks.

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Like, we can definitely, you

know, quadruple the pace at least.

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So, uh, that's one of my arguments,

you know, for the accelerator.

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Okay, so in that video I'm like, "Okay,

the ac- you know, the Google Data

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Analytics Certificate is fine, but it's

not really gonna help you land a data job.

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If you want help to land a data

job, you should do the SPN method.

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You know, learn the skills, build

projects, uh, grow your network.

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If you want to do that with mentors and

with friends, you know, come and join the

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Data Analytics Accelerator, um, and do

it with me, and I'll teach you everything

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I know and help you land a data job."

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So you, you hear that, you know, that

whole pitch, and, uh, tell me, I guess,

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like what was your thoughts on it?

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Uh, and then I guess you can tell

the story of, of how you made sure

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that it wasn't necessarily a, a scam.

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Um, it's pretty funny.

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Um, so it was like some

type of demo, right?

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You were…

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It was a video, and there was like a chat-

a chatbot, what I thought was a chatbot.

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Um, "If al- if you have any

questions, just let us know."

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And I was chatting, and then I

watched the entire video, and I

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was asking a lot of questions.

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And then you were saying it

was you, you know, the one that

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was answering m- my messages.

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So I was like, "Prove it," you know?

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Like, "Send me a picture so

I can know that it's you."

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And you send me a video of you,

like, getting ready and having a

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burrito heated in, in the microwave.

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I wa- I was like, "Okay, so

this guy is eating a, a burrito.

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That's fine."

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And I swiped my credit card,

and was a great investment.

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Wait.

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Okay, yeah.

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Now I remember what you're talking about.

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Yeah, so you joined.

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I do, like, a, a free training.

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We'll have a link in the show notes

down below where, uh, like you join,

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and I basically give you this one-hour

training of how to become a data analyst.

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And in there, a chat widget

that, that goes to my Slack.

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And so if I'm available, I

respond via Slack, right?

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If I, if I'm not

available, I don't respond.

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Okay, and so you're like, "Is

this AI or is this Avery?"

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And it ac- Yeah.

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And that's how I proved.

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Okay.

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Good I was eating a burrito that day.

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I've gotten more into Asian bowls

recently in the microwave, but.

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Same.

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Okay, so then you join the accelerator,

so you're in, you're in our boot camp,

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and I guess what, what did you feel

like you got out of the boot camp?

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I know that you, you mentioned, like,

you feel like Excel, your Excel skills

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were, were still a little bit weak.

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So in module two, right away, we build a

project on some sales data using Excel.

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So did you find that whole

module pretty helpful?

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Yeah, it was pretty helpful, but I

think the most helpful was actually

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having someone, like, to ask a

question, to get good mentorship.

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Like, Trevor was amazing.

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Um, Isaac was amazing.

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You were amazing, too.

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Um, and I think that's a lot of value,

because I can just send a WhatsApp

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message and get an answer, right?

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Like, "Hey, I'm stuck here," or,

"Hey, I'm applying to this job."

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What should I do?

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Get prepared for the interview, like

practical interviews, stuff like that.

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So you f- Um- You found the mentoring

to be, to be the most helpful.

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Yes.

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I'm not self-taught, really.

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Um, I'm not really self-taught.

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I need to be held accountable by somebody.

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Maybe there's people that

they're self-taught and they

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watch hundreds of YouTube videos

and they be- become experts.

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I tried, I failed.

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Um, but just, like, actually getting

that motivation to do something, not

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just say that you want to do something.

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Like, do it and then say

whatever, but try it at least.

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Mm.

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I, I love the humility that, that you

have to say, "I'm not self-taught."

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I don't think I'm

self-taught- No … either.

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I think I've had an episode

where I say, "I think self-taught

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is a fallacy," and it's…

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People wear it as a, a badge of honor,

and it's like, why is that cool?

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Like, oh, so you spent a lot of

time learning something you could

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have learned faster on your own?

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Like, good for you.

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Like, there's no award in life that

actually, like, that makes you…

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Like, it makes being self-taught worth it.

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And also, I don't think there's anything

really truly self-taught, 'cause it's like

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you learn from somewhere, like, whether it

was a, a, a boot camp- Somewhere, someone

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yeah, a university.

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It's not like you just sat down and you

were like, "God of data, please teach

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me how to make tableau charts," and

then poof, you, like, figured it out,

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and I guess even then that was God.

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So I don't know.

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I, I, I tried it and I failed, so I know.

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I, I love that.

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Um, I'm curious, so in the

Accelerator, uh, we have a couple

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different ways to, to get help.

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We have an AI bot in the program-

Mm … that's trained on our lessons.

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We have our community forum

where you can ask questions.

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We have comments on all of our

technical lessons where you can,

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where you can ask questions.

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We have the live office hours.

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We have email support.

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Um, which one of those

did you take advantage of?

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Uh, all of them, any of them?

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Which one did you like the most?

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All of them.

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Like, all of them, but the best

was for sure the weekly meetings.

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Um, I forgot the name of the- Yeah, just

office hours … the weekly office hours.

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Yeah.

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Yeah.

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So that was the best, and just

also chatting, like, one-on-one

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with Trevor helped me out a lot.

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Um, also, um, sharing

questions, posting my overall…

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Because just so you know, if you look

at my social media, I don't post shit.

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I just share memes.

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That's all I do.

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Um, so it was really hard for me to,

like, start- Doing stuff like interacting

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with other people on LinkedIn, that was

like the hardest for me beyond learning

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how to code or to use Excel, honestly.

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Okay, very cool.

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That's, that's awesome to hear.

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Yeah, I, um…

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You, you were pretty-- I mean, you,

you were pretty decent at, at posting

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inside the community and asking us

questions and sharing with, with everyone.

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One, one of the things, one of the

posts I, I pulled up from you, um,

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was when we first rolled out our AI

support tool, um, inside of the program.

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Uh, that helps…

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One of the things it helps you do

is, um, rewrite your resume bullets.

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So y- the title of the post was "Use

the Data Fairy Tool If You Haven't,

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uh, Yet," and you mentioned that

you were applying to a lot of jobs

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but not getting a ton of responses.

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Uh, and then you used Data Fairy to

highlight your previous experience and how

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that adds value to a data analyst role.

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Um, "Surprisingly, I started

receiving emails from recruiters

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wanting to schedule interviews.

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This week I have six interviews lined up.

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I'm currently on module five, and

even if none of these interviews

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lead to an offer, I'm in a much

better place than I started."

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So, um, that's super good,

good to hear that, that, that

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tool was useful, uh, for you.

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I'm curious, so you're, you're applying

to roles, you have this HR experience,

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you know, you're, you're trying to

revamp your resume using some of the

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AI tools that, that we have here.

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Tell me about, a little bit more about

the journey that eventually, you know,

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led you from this HR role to landing

a billing analyst role internally

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inside of your company, which is one

of the things we talk about in module

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one, where like one of the best things

you can do is transfer internally.

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Talk through like how that

process was and how you actually

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landed that, your first data job.

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Yeah.

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So I was doing a lot of reporting, like

maybe like 12 reports every week, right?

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Um, manual reports and

scheduled reports and whatnot.

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Um, then I had my yearly review

with the director of operations

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for Global Business Services.

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Um, and I was just talking to him,

"Hey, what, what's the next step?

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I've been here for three years now.

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How can I grow?"

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Right?

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And I've been asking that question

for like over a year and a half.

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And he was saying, "Oh, it's

because there's not a lot of,

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or any, um, open opportunities.

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Like right now we're looking for a

billing analyst that can know how to use

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Excel and this, this, this and that."

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I was like, "But I know how to do that."

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And he was like, "Oh, really?

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How did you learn that?"

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And I was like, "Well, I did a, like a

bootcamp and learned, I learned a lot.

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I learned about Python, about

R, SQL, Tableau, advanced Excel

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skills, to if I'm, if I'm honest."

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Um, and he was like, "Oh, really?

306

: 00:13:58

I didn't know about that."

307

: 00:13:59

And the reason why is because

they don't update the resumes.

308

: 00:14:03

Like the resume that I applied for on

that job back in: 2023

309

: 00:14:08

use that for internal purposes, but

that's not who I am anymore, right?

310

: 00:14:13

Um, and then I got a, an interview.

311

: 00:14:15

They're corporate, by the way.

312

: 00:14:17

Um, then I got another one, and then

I got the job and they were asking me,

313

: 00:14:21

"How do you see yourself in five years?"

314

: 00:14:23

And I s- said, "As a solutions architect."

315

: 00:14:26

And they were just saying, "Oh,

I just want to confirm that I'm

316

: 00:14:28

investing in the right person."

317

: 00:14:29

Right?

318

: 00:14:30

But that really helped me out.

319

: 00:14:31

I did a lot more of Excel

work, lots more of audits.

320

: 00:14:35

Um, they actually have daily SQL

integrations with like Workday, um,

321

: 00:14:40

on a daily basis, and you will see

errors and you will then fix them.

322

: 00:14:43

Okay.

323

: 00:14:44

Awesome.

324

: 00:14:44

So at that role, um, you were using

Excel, uh, quite a bit, and I also saw

325

: 00:14:50

some Power BI on your resume as well.

326

: 00:14:51

Was that more for like the

reporting side of things?

327

: 00:14:54

Yeah.

328

: 00:14:54

Um, it's just so, so much data,

like for different clients.

329

: 00:14:58

Like I will audit six different

accounts, six different

330

: 00:15:01

clients, different industries.

331

: 00:15:03

Like all these different

exceptions- Pay policies, states,

332

: 00:15:07

exemptions, markups, you name it.

333

: 00:15:09

I don't wanna bore you with this.

334

: 00:15:11

Um, but if you don't use something that

will make it easier for everyone to

335

: 00:15:16

understand, then what's the point, right?

336

: 00:15:18

You can have a really nice dashboard,

but if nobody understands what

337

: 00:15:21

you're trying to say, then what's

the point of the dashboard?

338

: 00:15:24

Yeah, 100%.

339

: 00:15:25

You know?

340

: 00:15:26

You mentioned a lot in the community,

um, and from me and you just talking

341

: 00:15:29

recently that, you know, sometimes you

were struggling to land interviews and

342

: 00:15:34

sometimes you had a lot of interviews.

343

: 00:15:36

Um, what do you feel like the biggest

difference, and maybe also from

344

: 00:15:38

your recruiting experience as well,

like actually looking at resumes and

345

: 00:15:41

applications and stuff like that,

what do you feel like was the biggest

346

: 00:15:44

experience going from not getting

interviews to getting interviews?

347

: 00:15:47

Like, what changed?

348

: 00:15:48

What were you doing differently?

349

: 00:15:49

The format.

350

: 00:15:50

The Data Fairy and the template that

you shared with us, um, it's really

351

: 00:15:55

cool because it highlights what you

have accomplished, your achievements,

352

: 00:15:59

not just what, what you did, right?

353

: 00:16:01

And here in Mexico, many other

countries do it as well, we have our

354

: 00:16:05

picture, we have images, we say Excel.

355

: 00:16:09

So it was a bit weird overall because

I was applying to jobs and I was

356

: 00:16:13

just getting rejected over and over.

357

: 00:16:16

I was, like, handling, like, 12

rejections a day for, like, a month,

358

: 00:16:19

and then I change it and it got better.

359

: 00:16:21

Wow.

360

: 00:16:22

So really it was just, like, resume

formatting, switching to one of the,

361

: 00:16:25

the resume templates that we give you,

and then what's the resume content,

362

: 00:16:29

like the bullet points essentially,

like making sure that the bullet

363

: 00:16:32

points on your resume are tying

closer to, like, data analyst roles.

364

: 00:16:37

Yeah.

365

: 00:16:37

For example, um, the whole thing

that I talked to you about, about

366

: 00:16:41

scheduled reports, about, um, monthly

business reviews, client-facing,

367

: 00:16:46

like what I did with that, how I

reduced errors by 45, 50% on the

368

: 00:16:51

billing side and also like data-wise.

369

: 00:16:54

Like if somebody is working remotely but

they're based in, let's say, California,

370

: 00:16:59

but the job is in Oregon, then the

pay policy should be different, right?

371

: 00:17:03

Um, instead of weekly 40,

it should be daily eight.

372

: 00:17:06

So you know, if it goes like that

for about six months it will be

373

: 00:17:10

like a big impact for the company.

374

: 00:17:12

Funny, it's funny that you say that

because, um, you know, one of the

375

: 00:17:15

things if I go to your LinkedIn and

I scroll all the way down, well the

376

: 00:17:17

first job I see is, is QA analyst.

377

: 00:17:20

And I don't know if that's actually what

your exact title was back then, um, but

378

: 00:17:24

we had an interview that we did with Jen

Hawkins who landed a job at Apple, and

379

: 00:17:28

everyone went to her LinkedIn page and

looked at her experience and she's like…

380

: 00:17:32

And they were like, "You didn't

help her become a data analyst.

381

: 00:17:34

She's already been a

data analyst for years."

382

: 00:17:36

And I'm like, "You guys,

that's like the exact point.

383

: 00:17:38

Like that's the whole reason like the

accelerator worked is we did such a good

384

: 00:17:42

job at disguising her past experience to

look like they were data analyst roles

385

: 00:17:47

and that's why she was able to land

data analyst interviews and actually

386

: 00:17:50

land her true first data analyst role."

387

: 00:17:52

So it's like if you could actually

change your bullet points and even your

388

: 00:17:56

titles to sound more data analysty,

that's how you land more data analyst

389

: 00:18:01

interviews and that's how you actually

get your first real data analyst job.

390

: 00:18:04

And, and if someone looks at their, your

resume or your LinkedIn and they're like,

391

: 00:18:08

"This person's been a data analyst for

years," that's how you know we did a

392

: 00:18:10

good job of, of disguising the resume.

393

: 00:18:13

So s- that makes a lot of sense.

394

: 00:18:15

Um, I'm curious though because like there

were some times where you weren't, you

395

: 00:18:18

know, like you said, you were applying,

you got like 12 rejections a day.

396

: 00:18:20

How'd you stay positive

during all of that?

397

: 00:18:22

I didn't stay positive.

398

: 00:18:24

That's the thing.

399

: 00:18:25

Um, it got me down.

400

: 00:18:27

At w- at what point, I didn't apply

to any jobs for about a month.

401

: 00:18:30

I was like, "What's the point

of applying if I'm gonna be

402

: 00:18:32

rejected either way," right?

403

: 00:18:34

Um, I used that time to,

like, improve my skills.

404

: 00:18:38

Um, and one thing that I can tell

you that helped me out the most

405

: 00:18:42

from DAA was learning the structure

of making a good project overall.

406

: 00:18:47

Like, yes, we make projects in Excel, in

Tableau, and different tools, SQL too,

407

: 00:18:52

but if we add our own spice to it, you

know, our own signature if you wanna call

408

: 00:18:58

it, like something that you, you like.

409

: 00:19:00

I like, I like soccer.

410

: 00:19:02

We call it football here, but I'm,

I'm just call, gonna call it soccer.

411

: 00:19:04

If you do something related to soccer

or something to turn over something

412

: 00:19:08

that you- you're actually passionate

about, about like, "Hey, why were so

413

: 00:19:11

many layoffs between 2024 and 2025?

414

: 00:19:14

What was the main change?

415

: 00:19:16

What happened?"

416

: 00:19:17

You know, between '23 and '24 and '25.

417

: 00:19:20

And, you know, looking at those pa-

uh, at those patterns, I don't have,

418

: 00:19:23

like, a live project portfolio for

those specific projects, but I will

419

: 00:19:27

share those projects according to

the job that I was applying for.

420

: 00:19:31

I was like, "Okay, if I'm

applying to HR, I'm just gonna

421

: 00:19:33

have HR and payroll projects.

422

: 00:19:35

If I'm applying to more data, I'm

just gonna add, you know, data

423

: 00:19:38

projects about stuff that I'm actually

knowledgeable about," like Pokemon

424

: 00:19:42

cards or, you know, soccer, sports,

stuff that I actually like, and I

425

: 00:19:47

kinda made it like a hobby of mine.

426

: 00:19:49

Um, you're mixing a hobby that

you're passionate about with

427

: 00:19:52

what you're learning, so that way

it's, like, the best mix to learn.

428

: 00:19:56

Yeah, I mean, that was,

that was well said.

429

: 00:19:58

That's like in- inside of the accelerator

we have like a mini course called,

430

: 00:20:01

like, Data Project and Portfolio

Bible, and that's, like, better than

431

: 00:20:05

the way I say it in the lesson in

there where it's like, "Yes, we do all

432

: 00:20:08

these projects inside the accelerator.

433

: 00:20:09

You know, you should use those.

434

: 00:20:11

You sh- those are good projects, but

the best projects are the ones that

435

: 00:20:14

you're going to create on your own.

436

: 00:20:15

And hopefully after we've walked you

through the steps of how to do a project,

437

: 00:20:19

how to do the write-up, how to publish

it and all those things, you'll be able

438

: 00:20:21

to do them on your own a lot easier."

439

: 00:20:23

And specifically you do that at

the end with your capstone project,

440

: 00:20:25

and those are the projects I think

that really make you stand out.

441

: 00:20:28

Um, and like you said, they're the ones

that are more fun, 'cause it's like I'm

442

: 00:20:31

not part- like, one of the projects we do

i- in the accelerator program is, like,

443

: 00:20:35

World Bank data, and it's like I'm not

really passionate about World Bank data.

444

: 00:20:38

And I'm glad that I have that on

my, my portfolio, but it's like I'm

445

: 00:20:41

much more interested in, like you

said, Pokemon cards or sports or

446

: 00:20:43

something, you know, more up my alley.

447

: 00:20:45

And I think recruiters can really

see that passion, that passion as, as

448

: 00:20:49

well when you're actually applying.

449

: 00:20:51

Okay.

450

: 00:20:51

Now tell me, like, how you actually landed

this role that you, you just started the

451

: 00:20:58

other day, like with this AI data company.

452

: 00:21:00

Tell me, like, how did you actually…

453

: 00:21:02

Did you find them?

454

: 00:21:03

Did they find you?

455

: 00:21:04

What was the interview process like?

456

: 00:21:06

Um, how did that go?

457

: 00:21:08

It's gonna be very funny,

so if I laugh, I'm sorry.

458

: 00:21:10

Um, the role that I applied for was

nothing to do with this job title Okay.

459

: 00:21:17

It was for a payroll analyst job title.

460

: 00:21:20

Okay.

461

: 00:21:20

Different job description,

different everything.

462

: 00:21:22

Uh-huh.

463

: 00:21:23

So here's the, the, the fun part.

464

: 00:21:25

I did get the interview.

465

: 00:21:26

You know, I, I found the job.

466

: 00:21:28

I applied.

467

: 00:21:29

I used the whole last posted

24 hours- Yep … remote and

468

: 00:21:34

according to what I'm looking for.

469

: 00:21:35

I applied to the job.

470

: 00:21:37

Within two weeks, I got a,

a call from the recruiter.

471

: 00:21:39

She was- she's the best recruiter

I've ever had an interview with.

472

: 00:21:43

Like, she was, like, really human

about the whole process, and I'm,

473

: 00:21:46

I'm gonna tell you why in a bit.

474

: 00:21:47

So it was for a payroll analyst

position, and I was doing the

475

: 00:21:52

interview with the recruiter.

476

: 00:21:53

She said, "Oh, you have

a great background.

477

: 00:21:55

I love your, your energy," you know.

478

: 00:21:58

And then I got an interview with, um,

another manager, and then she really

479

: 00:22:05

liked my energy, my background experience.

480

: 00:22:08

She was making me a couple questions.

481

: 00:22:10

And then long story short,

I didn't get that role.

482

: 00:22:13

They said the, the role moved to India.

483

: 00:22:15

But she said, and I quote,

"I'm trying each and every way

484

: 00:22:18

to get you to work with us."

485

: 00:22:19

That's what the recruiter said,

and I was really grateful for that.

486

: 00:22:22

Like, there were days of…

487

: 00:22:23

Like, two days I didn't know anything.

488

: 00:22:25

I was, like, sending her an

email, and she was, like, really

489

: 00:22:27

responsive with my emails.

490

: 00:22:29

No more than a day to,

to reply back, you know.

491

: 00:22:32

Um, super professional as well.

492

: 00:22:34

Then I got an interview with someone

from the AI and robotics team, and

493

: 00:22:39

they said that I was gonna take

over the payroll for their team, but

494

: 00:22:42

that's, that's what I was assuming.

495

: 00:22:44

And then I got an interview with,

I didn't know, he was a director of

496

: 00:22:48

operations and AI for that company.

497

: 00:22:51

But I was talking to him like,

"Hey, dude, how's it going?"

498

: 00:22:53

You know, like if he was

a long friend of mine.

499

: 00:22:55

Then I was having different questions

asked to me like, "Oh, how long

500

: 00:22:59

have you been working remote for?

501

: 00:23:01

Are you based in Mexico?

502

: 00:23:02

What part of Mexico?

503

: 00:23:04

What do you do outside of work?"

504

: 00:23:05

There were really no technical

questions in that interview.

505

: 00:23:08

They were just asking who I am, what

I like to do outside of work, and, you

506

: 00:23:12

know, how long I've been working for,

what's my background, stuff like that, but

507

: 00:23:17

never, like, actual technical questions.

508

: 00:23:19

But he even said, like, "Oh, I already

done my, my research, and I think

509

: 00:23:22

we're gonna move forward with you."

510

: 00:23:24

Fast-forward, I didn't hear anything

for about two weeks, three weeks.

511

: 00:23:27

I was like, "Okay, that's it," you know.

512

: 00:23:29

"I'm done for."

513

: 00:23:30

Um, then the recruiter calls me and say,

"Hey, they want to offer you the job."

514

: 00:23:34

I'm like, "Okay, payroll analyst."

515

: 00:23:35

And then I see the offer,

which I share with you.

516

: 00:23:38

I was like, I was like, "Maybe

this is a mistake, you know.

517

: 00:23:41

Hey, are you sure?

518

: 00:23:42

Like, maybe it's, you know, something

different for somebody else.

519

: 00:23:45

Maybe you made a mistake."

520

: 00:23:46

But then she was like, "No, he's

a- she's actually offering you

521

: 00:23:50

that position with this team."

522

: 00:23:51

I was like, "Oh."

523

: 00:23:52

I was, like, speechless during that call.

524

: 00:23:55

And I was like, "Okay, just give me a

few," and then I just cried, you know.

525

: 00:23:58

I was like, "What the heck?"

526

: 00:23:59

Yeah.

527

: 00:24:00

That's why it was…

528

: 00:24:00

It's, it's funny and emotional at

the same time be- because, you know,

529

: 00:24:05

I wasn't expecting that at all.

530

: 00:24:07

Yeah.

531

: 00:24:07

That's, that's very interesting.

532

: 00:24:08

There's so many different things I

like that you did in that process

533

: 00:24:11

that I think served you well.

534

: 00:24:13

One was you were looking for roles

that weren't just data analyst, right?

535

: 00:24:17

'Cause those get really swamped, but like

payroll analyst, and benefits analyst,

536

: 00:24:21

you know, HR analysts, billing analysts.

537

: 00:24:23

Those are different roles that

you were looking for, and I think

538

: 00:24:25

that, that served you really well.

539

: 00:24:27

And then two is you didn't let the

rejection get you down 'cause they,

540

: 00:24:30

like, did say no to you, right?

541

: 00:24:31

Like, they, they moved

the role somewhere else.

542

: 00:24:34

Um, but, like, that relationship-

Yeah … you were able to, to garner

543

: 00:24:37

and stay positive and kinda nurture, you

know, obviously turned to this, this new

544

: 00:24:40

role, um, this new AI data role, which

I think is, is really exciting for you.

545

: 00:24:45

So, I mean, good on you for, for

keeping the relationship alive, staying

546

: 00:24:49

positive through that process, and

looking for, you know, fresh jobs

547

: 00:24:52

that aren't just data analyst jobs.

548

: 00:24:54

So that, that makes a lot of sense.

549

: 00:24:55

You just started this job, so w- I'm not

gonna ask you, like, what you do on a

550

: 00:24:59

day-to-day basis or what tools you use

'cause you will, you will figure that

551

: 00:25:02

out as you go, uh, through, through

this job down through the future.

552

: 00:25:06

You know, one of the things that

you posted in the community when you

553

: 00:25:09

landed this job, kind of announcing

this, like, two to three weeks

554

: 00:25:12

ago, um, you know, one of the…

555

: 00:25:14

You gave some advice to the

rest of our, our students.

556

: 00:25:16

One of the things you said is

build something you were generally

557

: 00:25:18

curious about, and I think we

talked about that, um, here.

558

: 00:25:21

Yeah.

559

: 00:25:21

Another thing that you, you talked

about was stay consistent on

560

: 00:25:25

LinkedIn even when engagement is low.

561

: 00:25:26

Can you talk through, like, why

you feel like it's important to,

562

: 00:25:28

to post on LinkedIn and, and to

kinda get yourself out that way?

563

: 00:25:32

I'ma keep it short.

564

: 00:25:33

That's what re- recruiters see when

you apply for a job on LinkedIn.

565

: 00:25:36

Just honestly, like, if, if

you're active, if you're posting.

566

: 00:25:39

It's kinda like a…

567

: 00:25:40

I wanna call LinkedIn, like, a

mini resume/Facebook page because

568

: 00:25:45

you, you could post memes, you can

post something about work, but just

569

: 00:25:49

staying active really means a lot.

570

: 00:25:50

And you, you never know, maybe your…

571

: 00:25:52

you, you go viral on the post, right?

572

: 00:25:55

And you get noticed by that

from re- different recruiters.

573

: 00:25:59

And I was getting reached out

by recruiters, but they were not

574

: 00:26:01

good roles, just being honest.

575

: 00:26:03

But none of my posts went viral at all.

576

: 00:26:06

I think the max that I got

was, like, nine reactions, 12.

577

: 00:26:09

But I, I did notice a big difference in

my connections and people messaging me.

578

: 00:26:14

Even though it looks like it's like

a ghost town on my LinkedIn page, it

579

: 00:26:18

did make a difference, and I'm really

grateful that I was pushing for at least

580

: 00:26:22

two months straight, posting almost

every day, like Monday through Friday.

581

: 00:26:26

It helped me out, boost

my visibility on LinkedIn.

582

: 00:26:29

Yeah Very cool.

583

: 00:26:30

I like that you said that.

584

: 00:26:31

That's what we're curious to see.

585

: 00:26:32

It doesn't matter if it only, you

know, if you get 12 likes and it

586

: 00:26:35

gets, you know, 800 impressions.

587

: 00:26:37

You only need one

impression to get the job.

588

: 00:26:39

Um, and you're- Yep … just fishing for

the, the right, the right impression.

589

: 00:26:43

What other advice, you know, would

you give people who are maybe in

590

: 00:26:46

a similar shoe, uh, uh, to you?

591

: 00:26:49

Like maybe, maybe specifically there's

a lot of people who listen and they

592

: 00:26:52

talk about, you know, "I wanna work.

593

: 00:26:54

You know, I live not in the US," maybe

it's Mexico, maybe it's whatever country.

594

: 00:26:58

"I wanna work for a US company."

595

: 00:27:00

I'd be curious to know like what advice

you'd give, 'cause obviously you've

596

: 00:27:02

done that pretty well in your career.

597

: 00:27:04

Yeah.

598

: 00:27:04

So for my 11 years of experience

working with US companies, I can

599

: 00:27:09

say you need to say yes to jobs that

you're not gonna love them, right?

600

: 00:27:15

At first glance, it's gonna

just give you one step closer

601

: 00:27:18

to what you're looking for.

602

: 00:27:20

But you need to say yes to awkward

positions that you're not super

603

: 00:27:25

attracted to because that's

how you gain experience, right?

604

: 00:27:28

So just stay consistent

and adapt to the culture.

605

: 00:27:32

You're gonna talk with people from

different countries, not just the US.

606

: 00:27:35

Um, in my previous job I talked

with people from the US, from India,

607

: 00:27:39

from Canada, from, from the UK.

608

: 00:27:41

You name it.

609

: 00:27:42

The different cultures, different

ways of working, you have to adapt.

610

: 00:27:45

So just be open-minded when it comes to

applying to jobs for y- US based clients.

611

: 00:27:51

And even though if you get a no,

you're closer to, to the yes.

612

: 00:27:54

You already have the, the no already.

613

: 00:27:56

So it's like a more of a sales mindset

if you wanna call it like that.

614

: 00:27:59

You already have the no.

615

: 00:28:00

You just keep, um, you know, trying.

616

: 00:28:02

Like doing something is better

than doing nothing always.

617

: 00:28:06

100%.

618

: 00:28:07

I, I think you bring up a good

point, that it's really hard…

619

: 00:28:09

If you're trying to pivot two things at

once, you're trying to pivot the country

620

: 00:28:13

you work for and the role that you do,

if you're trying to do both those things

621

: 00:28:17

at once, that's probably too much.

622

: 00:28:19

It's probably, like, too

big of a home run swing.

623

: 00:28:21

You probably need to try to do something.

624

: 00:28:23

Choose one first.

625

: 00:28:24

Like, become a data analyst in

your home country, and then try

626

: 00:28:28

working for an American company.

627

: 00:28:29

Or like you said, and like you did

in your career, work whatever career

628

: 00:28:33

you have right now for a American

company, and then pivot to data from

629

: 00:28:38

within that company, like you did.

630

: 00:28:39

Like, you did that internal pivot

to your first billing analyst role.

631

: 00:28:42

Um, I think that makes a lot of sense.

632

: 00:28:44

What other advice would you

give to people who are maybe

633

: 00:28:46

in a similar shoes, uh, to you?

634

: 00:28:48

Maybe they're trying to be- become

self-taught data analysts right now.

635

: 00:28:52

Maybe they're struggling

to get any, um, interviews.

636

: 00:28:56

What advice would you give them?

637

: 00:28:57

You need to find a good structure.

638

: 00:28:59

If you're just applying because

you want to apply, you're n-

639

: 00:29:02

really not gonna get good results,

at least not on the long term.

640

: 00:29:06

Um, if you start with a good structure

from scratch, like, on the midterm,

641

: 00:29:10

long term, depending on how hard

you work, you will eventually get

642

: 00:29:14

where you're trying to, to go.

643

: 00:29:16

For example, I…

644

: 00:29:17

It took me, like, nine to 12 months.

645

: 00:29:19

I had, like, a three-month

break, um, because I was going

646

: 00:29:22

through some personal stuff.

647

: 00:29:23

But when I started working again,

like, every single month I was showing

648

: 00:29:27

up and working hard for it and, like,

embracing, like, awkward situations

649

: 00:29:32

where I had to post and comment on

LinkedIn with people that I don't know.

650

: 00:29:36

That's when I got a positive impact.

651

: 00:29:38

It was not, like, right away.

652

: 00:29:40

Took two, three months to see a positive

impact, but it really helped out.

653

: 00:29:45

You know, always, if you do something,

if you show up, you will eventually

654

: 00:29:49

get where you're trying to, to, to go.

655

: 00:29:51

But again, you can stop and not do

anything and keep yelling at, at the

656

: 00:29:56

screen and complaining, but you don't get

anything by, by complaining, you know?

657

: 00:30:00

Structure's re- really key.

658

: 00:30:02

I think it's hard to accomplish

any big goal without structure.

659

: 00:30:05

I'm supposedly training for my

third half Ironman, uh, this fall,

660

: 00:30:10

and I have no- How's that going?

661

: 00:30:11

Oh, I have no structure,

so it's not going well.

662

: 00:30:13

I, like, don't…

663

: 00:30:14

I lack a nutrition structure.

664

: 00:30:15

I don't have a workout structure.

665

: 00:30:17

I just kinda do it by the seat

of my pants, and, uh, I think

666

: 00:30:19

it's, I think it's showing.

667

: 00:30:21

I don't think I'm making any true

progress, and it's frustrating.

668

: 00:30:23

So just a plug, if you want that

structure, come, come follow the ESPN

669

: 00:30:26

method, uh, with the accelerator.

670

: 00:30:28

I'm curious, George, what advice you'd

give to people who, you know, are maybe

671

: 00:30:32

hearing about the accelerator for the

first time, or maybe have been sitting on

672

: 00:30:34

the fence, like, "Should I actually join

Avery's, you know, boot camp or not?"

673

: 00:30:38

What advice would you give them?

674

: 00:30:39

Hear him out the same way that I did.

675

: 00:30:41

I don't know if you still do it or not.

676

: 00:30:42

Like, it was, like, a, a demo

or a live video, and actually

677

: 00:30:47

breaking down everything.

678

: 00:30:48

Just at least listen to what he has

to say, and if you're interested,

679

: 00:30:52

you should definitely give it

a try because it helped me out.

680

: 00:30:55

Um, I tried different

courses, like the Google one.

681

: 00:30:57

It didn't help me out.

682

: 00:30:58

Um, and it feels, like, pretty cold, like

you're not actually talking with a person.

683

: 00:31:03

It's really, like, one-on-one with

Avery and Trevor and Isaac and the team.

684

: 00:31:07

That's what helped me out

the most, at least for me.

685

: 00:31:10

And just, you know, give it a try.

686

: 00:31:13

You n- you never know what's gonna happen

because, again, I'm not a self-taught.

687

: 00:31:18

I tried watching, like, hundreds

of YouTube videos, but I was, like,

688

: 00:31:20

dropping it on the spot always.

689

: 00:31:22

Well, I don't think you're

alone in, in that case, George.

690

: 00:31:24

I don't, I don't think

you're, uh, alone at all.

691

: 00:31:27

Yeah, I echo what George says.

692

: 00:31:29

You know, try me.

693

: 00:31:30

Send me an email and ask me to

say, "Are you actually AI or not?"

694

: 00:31:34

And see what food I'm microwaving,

uh, in the video I send

695

: 00:31:37

back to you in my response.

696

: 00:31:39

I'm, I'm happy to send more

burrito microwave videos out

697

: 00:31:42

there too to whoever wants one.

698

: 00:31:44

Go for it.

699

: 00:31:45

Go for it.

700

: 00:31:45

Um, George, this has been totally awesome.

701

: 00:31:47

Thank you so much for sharing your story.

702

: 00:31:48

We'll have your LinkedIn down

below in the description.

703

: 00:31:50

Is it okay if people reach out to

you with any questions they may have?

704

: 00:31:53

No worries.

705

: 00:31:53

Okay, awesome.

706

: 00:31:54

You guys can find George's LinkedIn

in the description down below.

707

: 00:31:57

Maybe follow him on LinkedIn.

708

: 00:31:58

Maybe give him a, a like on some

of his posts so he goes from

709

: 00:32:01

12 to 13, uh, re- reactions.

710

: 00:32:04

Yeah.

711

: 00:32:04

Uh, George, it was truly a pleasure.

712

: 00:32:05

Thank you so much for sharing your story.

713

: 00:32:07

Awesome.

714

: 00:32:07

Thank you.