128: Meet The Math Teacher Who Landed a Data Job in 60 Days (Thomas Gresco)

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I was applying to X amount of jobs a day or a week

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and just wasn't hearing anything.

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And I gotta be doing something wrong here.

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I felt like I had worked really

hard up until that point and

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I wasn't getting any results.

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Avery: And little did you know, two

weeks later, you're going to have

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a job that you're super stoked on.

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Thomas: I paid like 12 grand to learn

skills, which is how much you could

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pay for a master's program, which.

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In all likelihood, they also

don't set you up with the

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portfolio or networking, right?

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So essentially, I paid, I paid for

what would be the equivalent of

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a master's program and got none

of the portfolio or networking.

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that I could have done here

first for 11, 000 less and that's

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the only regret that I have.

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When we're talking about regrets,

that's the only regret that I have.

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Hi, my name is Thomas.

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Uh, I went from a high school math

teacher to a senior reimbursement

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analyst in less than 70 days.

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Avery: Thomas, I want to talk about

your whole journey from going from a

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high school math teacher to landing a

data job, but I want to start with, with

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a question or maybe more of a story.

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Um, but basically.

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You booked a one on one call

with me back in March of: 2024

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And I remember we did our first

phone call, uh, and I was like,

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Okay, yeah, high school math teacher.

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I asked these questions before so

I can be prepared for the call.

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So I saw like high school math teacher,

but you like knew a bunch of Data skills.

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And so we got on the call and I was

like, Oh my gosh, this guy is so

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close to landing a data job because he

has all the skills, but just doesn't

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actually have like the projects, the

portfolio, uh, and, and the network.

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So I was like, if he follows the SPN

method, he's going to land a job quickly.

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Uh, cause you'd be set.

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Did you feel the same way?

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Speaker 3: Yeah.

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And I think just our conversation

really drove me to joining your program.

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You know, I, I felt like you were

someone that could really help me

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because I had gone through, and we

talked about it, the, the Rutgers data

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science bootcamp, where I learned a

lot of these skills and some of them

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I had learned in my undergrad program.

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Um, but I just, I wasn't getting

anything, you know, I was applying to

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X amount of jobs a day or, or a week

and just wasn't hearing anything.

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And I was like, I gotta be

doing something wrong here.

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Or, or at least something

I could be doing better.

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And I felt like through our

conversation, like I could find

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something better in, within your program.

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And I think once I joined that

program, it really kind of.

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Kicked off for me where, you know, I, I

went through the, the skill stuff, like

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we, like you just said, wasn't, was pretty

easy for me, but then it was the building

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of the projects, the networking portion,

uh, the building the portfolio, which I

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think really helped me, uh, land this job.

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Avery: It's, it's interesting

you said that, cause I

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remember getting off that call.

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This was in March, uh, mid March.

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And I was like, man, this guy is such

a great candidate for the SBN method.

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I really hope he joins the

accelerator program so we can

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walk him through that path.

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Uh, but it still took you six

weeks to, to join the accelerator.

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What were you doing those six weeks?

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Speaker 3: Uh, so that was March.

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And then I guess I joined

one in May, I want to say.

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Avery: Yeah.

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Speaker 3: Okay.

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April.

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All right.

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You know, Oh, I remember.

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Um, so I was going on spring break.

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From, cause at the time I'm, I'm a

teacher and spring break was around

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Easter time, so middle of April or so.

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And I said to my girlfriend, if

I didn't have land any interview

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before that time, I was just going

to take a chance and join this.

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Um, so that's what I did.

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Uh, I didn't have an interview.

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Uh, I felt really, you know, not

down on myself, but just disappointed

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almost, cause I felt like I had

worked really hard up until that point

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and I wasn't getting any results.

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And, you know, it just kind

of made me want to join more

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and we got to that point.

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I was like, I'm going to do it.

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So I sat down, joined and just got

started and put my head down and

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kind of worked every single weekend.

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And also, it made it easier that it's

towards the end of the school year.

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I'm sure you remember or.

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Back in high school at the end of the

school year isn't really the toughest

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on, on the students or really even

the teachers are kind of winding down.

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So it was, it was easy for me to even,

you know, do work during the day too.

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Avery: Totally.

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I understand that.

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Um, you, you ultimately

joined the accelerator and.

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You landed a job as this senior

reimbursement analyst pretty quickly.

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Do you know how fast you landed that job?

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Speaker 3: Uh, so I started

the program in April.

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We said end of April and I got that job.

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I think I had the first

interview in the middle of June.

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So about a month and a half.

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Avery: Yeah, I guess I would say I had

from your start day of the accelerator to

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when you told us that you landed the job.

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I have a 61 days, so less,

less than two months.

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And you had been doing like, for

instance, like you said, this data

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science bootcamp through Rutgers,

like all, not all of last year, but

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you had done it the year previous.

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So, so basically.

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Like I said, you were

so close landing a job.

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You just need the SPN method.

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What is, do you feel like that's what

made the difference for you to like, to,

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to have land that job within two months?

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Speaker 3: Absolutely.

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I would, I would say definitely.

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Cause I felt like I had the

skills, like we just talked about.

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I just wasn't networking correctly.

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Uh, I wasn't doing what I had to do

on LinkedIn and you don't realize,

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you know, coming from the education

world, LinkedIn doesn't really exist.

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You apply for jobs and you go on the

interviews and you bring you know, stuff

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that you had done in other classrooms

or in my case because it was right

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out of college or in student teaching.

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Um, and that's pretty much it.

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Whereas for this, this

was all brand new to me.

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And the boot camp that I took, well all

good and well, I learned these skills.

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I had no idea what to do after.

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There was no You know, you should do this

to network with X, Y, and Z, or this is

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how you should show off your projects.

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It was just, we did a lot

of projects and a lot of.

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Uh, little tasks or homework

assignments, they called it,

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uh, but that was all on GitHub.

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And like you and I had talked about in

that first call, you're like, that's

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not really going to do anything for

you because no, um, employer or hiring

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manager is going to sift through a

bunch of code on your GitHub for like,

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it's just not going to do anything.

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Um, so I think SPN definitely made the

difference for me where, you know, I

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learned the skills, made these projects

and then was able to network and show

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off these projects in a really cool way.

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Avery: I think so too.

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I think, I think you were so close.

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You had all the skills, you just needed

the portfolio, uh, and the networking.

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Um, when I went through your LinkedIn

today to like kind of go through your

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whole journey, uh, you had posted once

about the, the data science bootcamp from

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Rutgers and it was at, at the very end.

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Yeah.

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I think it was maybe just like

the certificate or something.

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And that's so opposed to how we do it

inside of Data Analytics Accelerator,

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where like literally day one, I'm like,

post on LinkedIn, post on LinkedIn.

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You finish your first

project, post on LinkedIn.

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Uh, so I think that was

one of the big things.

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And that's ultimately how

you found this job, correct?

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Was someone reposted it on LinkedIn?

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Speaker 3: Yeah.

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So like you said, I had really

never posted on LinkedIn throughout

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that bootcamp, which is obviously

wasn't doing me any good.

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And then started posting on LinkedIn.

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Through the bootcamp or

through, um, our program.

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And then I just kind of followed people

who you interacted with on LinkedIn and

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found a lot of them to be posting jobs.

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And the one guy, I'm sorry,

I can't give him credit.

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I don't really remember his name or

who it was exactly, but he posted,

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I think like 10 or so remote jobs,

either weekly, every few days, and.

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I would just apply to them if I thought

I was a decent candidate for the job.

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Even if I wasn't really like a

super great fit in layman's terms,

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I, I just, I thought might as

well apply, can't hurt to apply.

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Um, so I applied, uh, to this specific

job and I was able to get an interview.

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I was honestly kind of shocked that

I got the interview with them, but

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that's, that's what I'm saying.

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Like you just, you never know.

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And I think it's really important

to apply and look at these posts.

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There's a lot of.

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You know, anecdotal stuff on

LinkedIn and you have talked about

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posting some stuff like that too.

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Um, in the, in the data career

jumpstart, but there are also a lot

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of people who are trying to help

us, like people that are looking

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for jobs where they're posting jobs.

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And I think that's really important

to look for and not to get too bogged

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down in, Oh, this isn't, For me,

because really it's for everybody.

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Everybody's doing it.

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You know,

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Avery: I think you had also

mentioned that that job that you

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ended up landing required, what,

two to three years of experience.

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Speaker 3: Yeah, it was 2 to 3 years of

some healthcare or medical experience,

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which obviously I'm a math teacher.

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I did.

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I just did not have, um, and I

can't I think that's what it said,

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but it said that in the actual

job description, but in the.

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Original post on LinkedIn

by the hiring manager.

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It said zero to two

years experience needed.

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So I was like, Oh, well the original

post says zero to two years.

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I don't really care what the

job description says right now.

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Let me just apply and see what happens.

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So I think don't get discouraged by

a lot of what job descriptions say.

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You know, a lot of that

could come from the top down.

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It might not even come

from the hiring manager.

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It could just come from.

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What the company as a whole

want that job description to say

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Avery: at the end of the day,

job descriptions are really more

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wishlist than they are requirements.

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So if you fit like 65 to 70 percent

maybe even 50 percent sometimes,

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you know, go ahead and apply, right?

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Because you never know what might happen.

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And that was true for you.

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And in this case, do you remember if

you was it like a linkedin easy apply?

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Was it that you did you

apply on their website?

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Speaker 3: Um, I applied on their website.

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So it was a link.

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I just clicked on the link

and I applied on the website.

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It was really simple.

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And I think you and I had actually

talked about this in the original call

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that we had in March, or even, I think

I talked to you again in April or so

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right around when I joined the program.

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It was the

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Avery: DM you sent me, I think.

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Speaker 3: Yeah.

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And it was, and you said just always

apply on, uh, the actual website.

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If you can, they're just more likely

to look at that than the LinkedIn,

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um, like easy apply algorithm.

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Avery: It's, it's super true.

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Um, having posted a job on LinkedIn

jobs, let me tell you, uh, LinkedIn,

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you need to hire a data scientist to

make your algorithm for candidates

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a lot better because I got over 550

applicants and the top applicants

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were not on the first two pages.

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I'll tell you that, like who

they thought was relevant.

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I was like, this person's not relevant.

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So that's great.

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Did you do anything special, cover letter,

send a cold message, anything like that?

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Speaker 3: Uh, definitely sent a cold

message and it was funny because, um,

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the person who interviewed me first,

uh, I sent a cold message to her boss

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and then she said, you know, honestly,

your, your resume was just passed to me.

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Like, I, someone got a message from

you and that's how I got your resume.

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And I decided to, you know, interview

and I was like, well, that's awesome.

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I guess that worked out for me.

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Um, but I don't think

I did a cover letter.

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Uh, we might've even talked about this.

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I think the cover letters, while they're

important, I guess they're way more

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likely to just read your cold message.

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If that's what you're sending them,

then they are your cover letter.

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Avery: Cold messages are

the new, uh, cover letter.

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I think cover letters are kind of dead.

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And if you can send a cold

message where it's like, I don't

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have to read one page of stuff.

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That's just mostly fluff that

you use chat GPT to write.

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And instead you can tell me and like.

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Three to four lines, who you

are, why I should care about you.

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I think that's so directly to my inbox.

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I think that's way more impactful.

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That's awesome.

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I didn't realize you sent a cold message.

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I think that's, I'm trying to figure

out like, you know, when, when Thomas is

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applying, I know you're a great candidate,

you know, you're a great candidate,

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but how do you convince this recruiter

and this hiring manager that When they

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have, you know, 500 other candidates

that you're the right candidate.

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And I think the cold message is one

and then probably your portfolio

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helped stand out a little bit.

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Speaker 3: Yeah, I would think so.

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I think just going back to the cold

messages, like I was sending one

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to every job that I applied to,

uh, or at least trying to, trying

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to find someone that I could.

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And I, I believe there's a page or a

couple of pages on our, on our, uh,

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Like in our book of materials that

you gave us where it just kind of

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gives you like an outline of what you

should say to these people and that's

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what I was, I had it bookmarked.

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I was going back to it every single time.

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Um, but yeah, they did talk

about my, um, uh, portfolio.

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I think it was probably

a sticking out point.

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Uh, you know, uh, person that

interviewed me first said it was

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definitely super interesting.

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And like I said to you, uh, she thought

that just based on that, that my

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analytical skills absolutely qualified

for the job that they were looking for.

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Avery: That's actually really cool

because, um, You know, you didn't have

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any healthcare experience prior to this,

but one of the things I tried to do when

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I designed the bootcamp was each module

has like a different industry theme.

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And so in module five, we, we cover

some healthcare data using SQL.

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So, you know, you, you'd maybe never

actually like in a workplace looked at

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healthcare records, but in this bootcamp,

we had looked over, I think there's like

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2 million rows in that, in that SQL data.

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Set that we, we analyze.

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So you had, you had at least some,

you created your own healthcare

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experience at the end of the

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Speaker 3: day.

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I think I actually said that I was

like, yeah, in my portfolio, uh, I,

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you know, I had this healthcare project

that we worked on, uh, you know, I

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tried to pull from family members too.

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I was like, I have some family that

works in healthcare and you know, you

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don't want to necessarily lie because

they could ask you follow up questions,

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but you certainly want to make your

knowledge look a little bit better.

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And I think that's what I tried to do,

especially using that project that we

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had worked on in the, in the class.

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Avery: Hey, experience is experience.

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No one can take it away.

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You can just describe it as it

is and they can decide whether

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they think it qualifies enough.

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But it's always good

to get that out there.

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Um, even with that, I think this is true.

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I haven't talked about that.

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I haven't talked to you about this before.

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Um, but, uh, I think after this first

interview, this, this timeline maps

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up a little bit, um, you went into our

community and you said, just finished the

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capstone and I had my first interview,

uh, this week, however, it seems like I

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don't have enough healthcare experience.

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So I'm not too confident if anything

else, it was a good interview experience.

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I'm continuing to apply for

jobs and sending cold messages.

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And you said this great line, some days

it's hard to not feel defeated, but

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definitely trying to stay as positive as

possible, hoping to land something soon.

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Was that, was that the first

interview for this job?

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Speaker 3: Yeah, that was the

first interview for that job.

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And I'm laughing thinking

about, thinking back to that.

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Cause I'm really, I got off the call

and I was like, wow, I have no shot.

303

: 00:14:40

I was like, I don't have

this healthcare experience.

304

: 00:14:44

And, uh, it just kind of all worked out.

305

: 00:14:46

I think that's the important thing.

306

: 00:14:47

Like, if we talked about this

a little bit, just go on these

307

: 00:14:50

interviews and kind of be yourself.

308

: 00:14:51

Um, I really talked about my

willingness to learn and want to learn.

309

: 00:14:58

And, um, I guess they liked that.

310

: 00:15:01

Um, and I, again, I was really

surprised and I was after that,

311

: 00:15:06

got the second interview and I

was pretty nervous for that too.

312

: 00:15:09

I was like, I wonder, I don't

even know why they're interviewing

313

: 00:15:11

me a second time right now.

314

: 00:15:13

Um, but that interview and I said it

when I got off it, I was like, I really

315

: 00:15:17

think that I might have just gotten

this and it wasn't anything technical.

316

: 00:15:23

Uh, they did ask a little bit about

my experience, but you just kind

317

: 00:15:26

of go into these interviews and

you kind of feel the vibe with the

318

: 00:15:30

people that you're going to work for.

319

: 00:15:32

And I just thought the vibe was great.

320

: 00:15:33

You know, I thought they'd be

great people to work for and it

321

: 00:15:36

got me really excited about it.

322

: 00:15:37

And.

323

: 00:15:38

You just say, here I

324

: 00:15:39

Avery: am.

325

: 00:15:40

I think that's so interesting and

I love that, that the interviews,

326

: 00:15:43

sometimes they're super scary, but a

lot of the times they're just like,

327

: 00:15:46

okay, does this person seem like

they have enough technical skills

328

: 00:15:50

and are they able to learn the rest?

329

: 00:15:51

I know that's one of the

things you mentioned.

330

: 00:15:52

It's like, maybe I don't know healthcare

yet, but I'm, I'm willing to learn that.

331

: 00:15:56

Um, I want to go back to that phrase.

332

: 00:15:58

Sometimes it is hard to not feel defeated.

333

: 00:16:01

Uh, what were you feeling

when, when you posted that?

334

: 00:16:04

Speaker 3: I think I

was a little bit upset.

335

: 00:16:06

Um.

336

: 00:16:07

Probably defeated, honestly, because

I just, I felt like this, when I'm

337

: 00:16:13

sure there are a lot of people like

me out there where, you know, you're

338

: 00:16:15

applying to so many jobs and you're

not hearing back that when you get that

339

: 00:16:18

first interview with that company, no

matter what company it is, you feel

340

: 00:16:22

like, all right, this is my shot.

341

: 00:16:23

I got to get this.

342

: 00:16:25

And that's how I felt with this company.

343

: 00:16:28

And I, like I said to you, I, I feel

like the first interview didn't go as

344

: 00:16:34

well as I, not that it didn't go well.

345

: 00:16:36

It just, I know what they were expecting

and I didn't think that was me.

346

: 00:16:39

So that, it kind of stunk.

347

: 00:16:42

Um, but at the same time, like I knew

how badly I wanted to change what I was

348

: 00:16:48

doing or change my career path, that it

was still driving me because, you know,

349

: 00:16:53

You know, I talked to my family about it

and they're like, well, even if you don't

350

: 00:16:56

get it, you're not just going to stop.

351

: 00:16:58

And I was like, yeah, you're right.

352

: 00:16:59

There's really no point feeling defeated

because I'm not going to just stop.

353

: 00:17:01

I, you know, you want to keep

going until you get that ultimate

354

: 00:17:05

goal of getting a new job.

355

: 00:17:06

And I think that's where the staying

positive portion is, is really.

356

: 00:17:11

Avery: Uh, I love the fact

that you didn't stop applying.

357

: 00:17:16

A lot of people land interviews

and then they stop applying.

358

: 00:17:19

Um, and it's so bad because when you

ultimately don't get that job, I mean,

359

: 00:17:24

you did in this case, but when you

usually don't get that job, you have,

360

: 00:17:27

you have to start all over again and

interview processes might take one month.

361

: 00:17:31

So it's like.

362

: 00:17:32

You, for one month, you basically

had no new applications, no new

363

: 00:17:35

interviews coming your way, and

you're starting over from scratch.

364

: 00:17:38

So I love that you,

that you kept applying.

365

: 00:17:42

Uh, let's talk a little bit

about your job that you have now.

366

: 00:17:45

Um, so it's senior reimbursement analyst.

367

: 00:17:48

Just go ahead and talk a little bit

about, you know, how you use data at

368

: 00:17:51

that job and what you actually do.

369

: 00:17:53

Speaker 3: Yeah.

370

: 00:17:54

So healthcare companies have contracts

with every hospital pretty much.

371

: 00:17:59

Um, and these hospitals contract us.

372

: 00:18:03

To maximize their revenue.

373

: 00:18:04

So what I do throughout the day is I read

through these contracts, uh, that the

374

: 00:18:10

healthcare companies in the hospitals

have, and I try to maximize revenue for

375

: 00:18:16

So we have what we have called a portal,

uh, where I do a lot of data validation,

376

: 00:18:21

uh, and data cleaning, meaning I go

through this year's contracts and probably

377

: 00:18:26

the contract from the year before, or

even two years ago, and I make sure

378

: 00:18:29

that these price points like make sense.

379

: 00:18:32

So, um, what does that mean exactly?

380

: 00:18:35

Like, if last year was.

381

: 00:18:38

You know, the maximum

price they would charge.

382

: 00:18:39

Let's just keep it simple.

383

: 00:18:40

It's 500 at 70%.

384

: 00:18:42

Uh, and this year I need to make sure

that they're not going to, I don't

385

: 00:18:47

know, 2, 000 at that same percentage.

386

: 00:18:50

It just wouldn't really make sense.

387

: 00:18:52

Uh, so that's where the, the

validation comes in to kind of make

388

: 00:18:55

sure that those numbers are correct.

389

: 00:18:57

And if I feel like they're super

off, then I'll contact the, uh,

390

: 00:19:00

the contacts that our company has.

391

: 00:19:01

Um, To make sure that this is

specifically what they want.

392

: 00:19:06

Uh, and then I do some work in Excel.

393

: 00:19:07

Uh, specifically with tables, not, not

actually really pivot tables, little

394

: 00:19:12

bit, little bit of pivot tables, but

more so table work, uh, VLOOKUPs.

395

: 00:19:17

Pretty much everything

that we do in your program.

396

: 00:19:20

Um, it's actually funny because

one of the, in training, uh, my

397

: 00:19:25

boss was talking about VLOOKUP.

398

: 00:19:26

So I was like, Oh, do

you guys use XLOOKUP?

399

: 00:19:28

And my boss was like, I

don't even know what that is.

400

: 00:19:31

And I was like, it just

makes VLOOKUP a lot easier.

401

: 00:19:34

That's all.

402

: 00:19:35

Um, so, um, a lot of the work is

done in Excel, uh, which I feel

403

: 00:19:40

like for most entry level data

jobs, it's perfect because you

404

: 00:19:44

don't know it until you actually get

into it, but Excel is, is perfect.

405

: 00:19:48

Pretty user friendly and you know,

you know how to do a lot of it.

406

: 00:19:51

Or at least what is

needed for the job tasks.

407

: 00:19:54

And anything you don't really know,

it's relatively easy to look up.

408

: 00:19:58

I'm not really making complex SQL code

yet or Python codes, but I'm kind of

409

: 00:20:04

looking forward to eventually jumping

into that and for this there is.

410

: 00:20:08

A lot of room to growth, but yeah,

that's what my day to day pretty

411

: 00:20:11

much looks like is just looking

through these contracts or, you know,

412

: 00:20:14

helping people with, uh, fixing up

Excel codes and things like that.

413

: 00:20:18

Avery: Well, that's one of the things

that we try to talk about in the

414

: 00:20:21

program as well, is just like, let's

get your foot in the door and then you

415

: 00:20:24

can learn the rest of it on the job.

416

: 00:20:26

And one of the things you mentioned,

uh, when we were talking before

417

: 00:20:29

the call was just like how

there's lots of room for growth.

418

: 00:20:31

At this company, there's lots of, uh,

different data roles that you could

419

: 00:20:35

eventually, you know, grow into as

you continue to, to have experience,

420

: 00:20:39

uh, as, as you, as you learn and

as you get better, uh, data skills.

421

: 00:20:44

Um, what, what other

differences has there been?

422

: 00:20:47

What other surprises has there

been from transitioning to like

423

: 00:20:50

a data role from a teacher role?

424

: 00:20:51

What has been a big surprise to you?

425

: 00:20:54

Speaker 3: I think the most

surprising thing or the thing that

426

: 00:20:57

I really have enjoyed the most

is just the flexibility of it.

427

: 00:21:00

Um, You know, I can log on at 8 o'clock

and, you know, then go take an hour

428

: 00:21:07

lunch or, or go take my car to get an

oil change if I need to, and then come

429

: 00:21:11

back and finish work at 4 or 5 o'clock,

whatever it is, just as long as you get

430

: 00:21:15

your work done, I feel like for me, at

least as a teacher, there is a lot of.

431

: 00:21:21

Not necessarily micromanaging, I guess

a little bit of it, but also there's

432

: 00:21:25

always something that pops up, right?

433

: 00:21:27

There's always something that popped

up in the school day where it just

434

: 00:21:30

kind of not necessarily derails your

day, but it makes, certainly makes

435

: 00:21:32

your life a lot more challenging.

436

: 00:21:34

And I'm not saying that can't happen at

this job, but it just feels like, you

437

: 00:21:40

know, your boss, trust, like my boss,

trust me, she gives me the work to do.

438

: 00:21:45

I go ahead and do it.

439

: 00:21:46

If I have questions, I message

her, you know, if not, we just

440

: 00:21:48

go about each of our days.

441

: 00:21:50

And that's something that has really

been not necessarily surprising,

442

: 00:21:54

but I guess a little bit because

I didn't really know how the

443

: 00:21:57

corporate world necessarily worked.

444

: 00:21:58

I've been so used to school for the last

X amount of years of my life, and that's

445

: 00:22:04

something that I've really enjoyed.

446

: 00:22:05

And then just obviously remote work is

it's nice that I could run downstairs.

447

: 00:22:10

Make a protein shake and then come

back upstairs and not miss a beat.

448

: 00:22:13

Avery: Not, not a whole lot of, uh,

remote work and teaching and also

449

: 00:22:16

not a whole lot of flexibility.

450

: 00:22:18

It's like, it's like if you, if you

want to start working at 7am, well,

451

: 00:22:22

there's like no students there at 7am.

452

: 00:22:23

If you want to start working

at like 9am or whatever, right?

453

: 00:22:27

There's like students who

have been waiting there for

454

: 00:22:29

like an hour or whatever.

455

: 00:22:30

So, uh, a little bit different in like

the data world, the, just obviously

456

: 00:22:35

like not really any shifts and, um, the

deadlines are more, more flexible, softer

457

: 00:22:41

than they would be in teaching because,

uh, that's just, that's just kind of how

458

: 00:22:44

business works versus how teaching works.

459

: 00:22:47

Speaker 3: Yeah, I just think

that you need to be able to

460

: 00:22:48

prioritize things, right?

461

: 00:22:50

Like, they'll give you

a list of things to do.

462

: 00:22:52

Uh, and you just kind of do your

best to, to get them done or to,

463

: 00:22:57

to do whatever they ask really.

464

: 00:22:58

And, and for the most part, like you

just said, it's, it's relatively soft,

465

: 00:23:02

you know, deadlines, unless, you know,

it's my boss might reach out to me and

466

: 00:23:05

say, Hey, I need this done by Wednesday.

467

: 00:23:07

Well, okay.

468

: 00:23:07

Then that's first priority, right?

469

: 00:23:08

You just change up what you're doing

and, and go from there, but it's

470

: 00:23:12

been, the switch has been awesome.

471

: 00:23:13

It has definitely been great.

472

: 00:23:15

Avery: Any regrets?

473

: 00:23:17

Speaker 3: Absolutely not.

474

: 00:23:18

I think I told you the only thing I really

miss is, is coaching, but I could always

475

: 00:23:21

go back to that if I really wanted to.

476

: 00:23:23

Avery: So, so you're pretty

happy in the new role.

477

: 00:23:26

Speaker 3: Definitely.

478

: 00:23:26

Definitely happy in the new role.

479

: 00:23:28

Um, I, I really like, and for any other

teachers, I think for me personally,

480

: 00:23:34

it was, I couldn't see myself.

481

: 00:23:36

In doing the same thing in the

classroom for the next 45 years,

482

: 00:23:41

because I didn't really want to be a

principal or, um, you know, a supervisor

483

: 00:23:45

or anything like that with here.

484

: 00:23:47

Like, we just talked about

there's there's so many different

485

: 00:23:49

opportunities for growth.

486

: 00:23:50

You know, I could be a pricing analyst,

or I could go and be just a normal

487

: 00:23:54

data analyst that they have here.

488

: 00:23:56

Um, you know, I could stay

and do this for a while.

489

: 00:23:58

And so on and so forth, but

there, there is a lot of different

490

: 00:24:01

opportunities for growth.

491

: 00:24:02

So definitely no regrets and something

that I'm really excited about.

492

: 00:24:06

I mean, I personally don't care.

493

: 00:24:08

What are they going to say to me?

494

: 00:24:09

Right.

495

: 00:24:10

I didn't know if you wanted to put that

out there for them, but I would just

496

: 00:24:14

like, well, yeah, go ahead and say it.

497

: 00:24:15

All I was going to say was like, I, I feel

like learning the skills is great and all,

498

: 00:24:20

but I also, you know, I don't know how

much we want to talk about, talk about

499

: 00:24:24

money on here, but I really, I think it

was, I paid like 12 grand to learn skills,

500

: 00:24:30

which is how much you could pay for a

master's program, which in all likelihood.

501

: 00:24:35

They also don't set you up with

the portfolio or networking, right?

502

: 00:24:39

So essentially I paid, I paid for

what would be the equivalent of a

503

: 00:24:42

master's program and got none of the

portfolio or networking that I could

504

: 00:24:46

have done here first for 11, 000 less.

505

: 00:24:51

And that's the only regret that I have

when we were talking about regrets.

506

: 00:24:53

That's the only regret that I have is

that I could have just started with this.

507

: 00:24:57

You know, I had a decent bit of skills.

508

: 00:25:00

That I already knew could have learned

it better through this and saved 11,

509

: 00:25:04

Avery: 000.

510

: 00:25:05

Let me ask you why you didn't

do that in the first place.

511

: 00:25:08

What, what was holding you back?

512

: 00:25:11

Speaker 3: So I don't think I really

knew much about what was out there.

513

: 00:25:14

I didn't do enough research to

find the best program for me.

514

: 00:25:20

I think I just, Honestly,

I just saw this ad.

515

: 00:25:23

I was like, Oh, I mean,

it's a six month program.

516

: 00:25:26

I only got to do it three days a week.

517

: 00:25:27

I'll learn some skills and I feel

like I'm going to job right after.

518

: 00:25:30

And I, I literally thought I'd be able

to get a job right after doing it.

519

: 00:25:33

Uh, and that's just, this is not how

it works, but I don't know if that's

520

: 00:25:36

me being naive or me just not really

knowing much about the corporate world.

521

: 00:25:40

Being a teacher.

522

: 00:25:42

Avery: I don't think it's you being naive.

523

: 00:25:44

I think, I think all these institutions.

524

: 00:25:47

Have good intentions.

525

: 00:25:49

Uh, I will say a lot of these institutions

use brand name to kind of woo you in.

526

: 00:25:56

So for example, I was a bootcamp

professor at MIT, right?

527

: 00:26:01

I wasn't employed by MIT.

528

: 00:26:03

In fact, all the people who

run the bootcamp were not ran.

529

: 00:26:06

They're not employed by MIT.

530

: 00:26:08

It was a third party service

that was basically promoting

531

: 00:26:12

MIT's professors recorded video.

532

: 00:26:16

Yeah.

533

: 00:26:17

Yeah.

534

: 00:26:18

Speaker 3: Because if you, I, if

I go to my professor's LinkedIn,

535

: 00:26:20

it doesn't say Rutgers university.

536

: 00:26:21

I think it's like edX

or something like that.

537

: 00:26:23

Avery: Yep.

538

: 00:26:24

Yep.

539

: 00:26:24

EdX is a, is a big one.

540

: 00:26:25

Um, so that's, that's one thing is like,

they're, they're kind of using brand names

541

: 00:26:29

and, and, and people trust brand names.

542

: 00:26:31

Like, I think that's another thing

with the Google analytics certificate

543

: 00:26:34

is it has Google's name on it.

544

: 00:26:35

So it must be good.

545

: 00:26:37

It's way too long.

546

: 00:26:38

It teaches you the wrong stuff.

547

: 00:26:39

There's not even a project.

548

: 00:26:40

There's no networking,

but it has Google's name.

549

: 00:26:42

So it has to be good.

550

: 00:26:45

Speaker 3: I was just going to

say, that's the other thing.

551

: 00:26:47

Like, I feel like your program

specifically focuses on what you

552

: 00:26:52

need to know right now to help you

get out of and where you need to be.

553

: 00:26:55

And then like we've talked about, you can

go and learn everything else after that.

554

: 00:26:59

Whereas this program that I did at

Rutgers, I, I swear to you, it was

555

: 00:27:04

Excel, VBA, Python, SQL, HTML, Java.

556

: 00:27:09

Machine learning all of it in a six

month period and it was just information

557

: 00:27:15

after information and you never

stopped to even think about what you

558

: 00:27:17

were going to do after this because

you were so bogged down in trying to

559

: 00:27:20

learn the information right now, right?

560

: 00:27:22

So there was no me thinking like, oh, I

have to go talk to somebody to help me.

561

: 00:27:26

You know, find a job here, or I need to,

um, display this better because the way

562

: 00:27:31

things like that are promoted is that

this, you're going to make a portfolio.

563

: 00:27:36

That's just your GitHub.

564

: 00:27:37

And like we've talked about, no,

no one is going to look at that

565

: 00:27:41

Avery: a hundred percent.

566

: 00:27:42

It's funny.

567

: 00:27:42

Cause I mean, I went through college

thinking the exact same thing, right?

568

: 00:27:46

Where it's like, Oh, those

teach me everything that

569

: 00:27:47

I'm going to use on the job.

570

: 00:27:49

Well, what you actually use on the

job and what you learn in college

571

: 00:27:52

are two very different things.

572

: 00:27:53

Uh, and I don't think

there's a whole lot of.

573

: 00:27:56

Time and thought going into a lot of these

programs of like, uh, we're just going to

574

: 00:28:01

teach them everything and we're just not

going to update the curriculum at all.

575

: 00:28:04

But like teaching, first off teaching

VBA, I think at this point is pretty dumb.

576

: 00:28:08

I think VBA is going pretty

extinct, uh, here in a second.

577

: 00:28:11

I don't think

578

: 00:28:11

Speaker 3: anyone uses it.

579

: 00:28:13

Avery: Yeah, it's, it's, there's

definitely some people out there.

580

: 00:28:16

Who are older, who are still using it.

581

: 00:28:17

But I think any coding is kind

of getting replaced by Python.

582

: 00:28:21

Even Microsoft's putting Python

inside of Excel, I think is a

583

: 00:28:25

pretty big admission on their part

that they see it going downhill.

584

: 00:28:28

Uh, learning HTML as any sort

of data professional, especially

585

: 00:28:31

early on is, is kind of silly.

586

: 00:28:33

That's not used very often.

587

: 00:28:35

There are.

588

: 00:28:36

Instances where you're using, where you're

creating like web applications, that it

589

: 00:28:40

is handy, but it's definitely not like

needed to land your first job or your

590

: 00:28:44

second job, the majority of the time.

591

: 00:28:45

So they kind of just throw

a bunch of skills at you.

592

: 00:28:47

And, and honestly, learning

the skills is fun and you feel

593

: 00:28:50

like you're making progress.

594

: 00:28:51

I think that's how I felt hard.

595

: 00:28:53

Yeah.

596

: 00:28:53

Like networking, like you, you are this

close to a job and you said, quote.

597

: 00:28:59

It's hard to not feel defeated.

598

: 00:29:01

And little did you know, two weeks

later, you're going to have a

599

: 00:29:03

job that you're super stoked on.

600

: 00:29:04

Uh, but learning skills feels good.

601

: 00:29:06

You can see progress networking.

602

: 00:29:08

You can't really see the progress.

603

: 00:29:10

Speaker 3: Yeah, unfortunately not.

604

: 00:29:11

Um, and you know what the funny

thing is, they didn't even

605

: 00:29:14

teach us R in that program.

606

: 00:29:16

R wasn't, we learned pretty

much everything, never R.

607

: 00:29:20

Avery: Oh, wow.

608

: 00:29:21

They just haven't.

609

: 00:29:21

Yeah, it was, it was

610

: 00:29:23

Speaker 3: some, I mean, we

did some really, really in

611

: 00:29:26

depth stuff, uh, for sure.

612

: 00:29:28

Uh, I mean, towards the end we were

doing machine learning, so I'm like,

613

: 00:29:31

I was training models and stuff

like that, which again, awesome,

614

: 00:29:34

but not gonna help me get a job.

615

: 00:29:38

Avery: By itself, that's.

616

: 00:29:39

Speaker 3: No, not by itself.

617

: 00:29:42

Avery: One of the things that we

talked about in the program at first

618

: 00:29:44

is like You're going to work like 90,

000 hours, uh, in, in your lifetime.

619

: 00:29:49

Do you really want to be doing something

that you don't necessarily love?

620

: 00:29:52

Um, so I'm glad, I'm glad you, you

made the investment and you bet on

621

: 00:29:56

yourself, uh, bet on your future.

622

: 00:29:58

You're like, I'm going to

enjoy these 90, 000 hours.

623

: 00:30:00

I'm going to, I'm going to be doing it

from home and not have to worry about.

624

: 00:30:03

You know, what parents are saying

about what I said to their kids

625

: 00:30:08

or vice versa or whatever, right?

626

: 00:30:09

Like, uh, live, live life a little bit

with more, more freedom and on your terms.

627

: 00:30:14

Okay.

628

: 00:30:14

Well, awesome, Thomas.

629

: 00:30:15

We'll have your LinkedIn information

and the show notes down below.

630

: 00:30:18

Can people reach out to you

if they have any questions?

631

: 00:30:20

Speaker 3: Yeah, absolutely.

632

: 00:30:21

Anytime.

633

: 00:30:22

Avery: Okay, sweet.

634

: 00:30:22

I think everyone needs to follow

Thomas's example, uh, here and, uh,

635

: 00:30:27

really focus on the cold messaging.

636

: 00:30:29

I think that was a big part and

the, the portfolio, uh, really the

637

: 00:30:33

P in the end of, of the SPN method.

638

: 00:30:35

Yeah, absolutely.

639

: 00:30:36

Thanks for being such

a good example of it.

640

: 00:30:38

Uh, we really appreciate it.

641

: 00:30:40

Speaker 3: Of course.

642

: 00:30:40

Anytime.

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