Artwork for podcast Data Career Podcast: Helping You Land a Data Analyst Job FAST
204: She Became a Data Analyst in 67 Days! (No Prior Experience)
Episode 20431st March 2026 • Data Career Podcast: Helping You Land a Data Analyst Job FAST • Avery Smith - Data Career Coach
00:00:00 00:40:34

Share Episode

Shownotes

Music therapist to Fortune 50 financial analyst in under 60 days. Here's exactly how Erin did it without a traditional background.

💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://datacareerjumpstart.com/newsletter

🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://datacareerjumpstart.com/training

👩‍💻 Want to land a data job in less than 90 days? 👉 https://datacareerjumpstart.com/daa

👔 Ace The Interview with Confidence 👉 https://datacareerjumpstart.com/interviewsimulator

⌚ TIMESTAMPS

01:20 – From music to Fortune 50

07:18 – What a good boss actually does

12:51 – 60 days from sign up to offer

20:18 – Applying while building skills

20:36 – One resume tweak, three interviews

23:03 – Stop only applying to remote jobs

28:39 – What the interview was like

34:40 – Do this if you're starting over

🔗 CONNECT WITH ERIN SHINA

🤝 LinkedIn: https://linkedin.com/in/erinshina/

🔗 CONNECT WITH AVERY

🎥 YouTube Channel: https://youtube.com/@averysmith

🤝 LinkedIn: https://linkedin.com/in/averyjsmith/

📸 Instagram: https://instagram.com/datacareerjumpstart

🎵 TikTok: https://tiktok.com/@verydata

💻 Website: https://datacareerjumpstart.com/

Mentioned in this episode:

💙 Thank you for subscribing

YouTube Channel

🚀 April Cohort — Data Analyst Bootcamp (Starts April 13th)

Ready to break into data analytics? Our April cohort kicks off with a live call on April 13th at 7pm ET where you'll meet your peers and mentors on day one. Save 20% when you enroll now, plus get LIFETIME access to our premium data job board. Join Today → https://datacareerjumpstart.com/daa

https://datacareerjumpstart.com/daa

Transcripts

Speaker:

You were working as a music therapist and

now you're able to work as a financial

2

:

analyst for a Fortune 50 company.

3

:

I am a financial analyst

at a healthcare company.

4

:

But you were able to land this,

this financial analyst role

5

:

pretty quickly signed up, clicked

submit on the accelerator package

6

:

like right before Christmas.

7

:

Started actually like doing the

program right after Christmas.

8

:

I.

9

:

Job was on March 1st, which

was a Wednesday, and then that

10

:

Friday I accepted my offer.

11

:

That's not even 60 days.

12

:

So one of the projects I think that

really helped me was the SQL Project

13

:

and the Accelerator, the, that was

something that I talked about in

14

:

all of the interviews that I had.

15

:

Today I'm really excited about my guest.

16

:

We have one of the, uh, members of

the data Analytics Accelerator who has

17

:

gone through a portion of the program

and landed a pretty sweet job that

18

:

we're gonna be talking about today.

19

:

Uh, my guest today is Aaron Sheena.

20

:

Aaron, welcome to the Data Career Podcast.

21

:

Thank you.

22

:

So happy to be here.

23

:

Yeah.

24

:

So excited that you, uh, agreed to come

on the show and talk a little bit, uh,

25

:

about your, your journey, which I think

is something that's really unique and

26

:

something that needs to be told because

you have a pretty interesting background.

27

:

Uh, you studied music in school,

but you no longer work in music.

28

:

So let's start off with what

you're currently doing now.

29

:

What do you do for work now?

30

:

Sure.

31

:

So, um, I am a financial analyst, um, at

a healthcare company, um, called Humana.

32

:

Uh.

33

:

Nationwide.

34

:

Um, and essentially I

work in risk adjustment.

35

:

Um, so basically looking at claims

data, the data that comes through

36

:

anytime you go to the doctor, um,

and make sure that we're analyzing

37

:

and filtering it correctly compared

to the government agency that runs.

38

:

Medicare, um, and making sure that

we are kind of aligning with them so

39

:

that we can predict how much we'll be

reimbursed for caring for those members.

40

:

Um, and so basically we then take that

analysis, um, and, uh, use it to help

41

:

us predict revenue and make projections

for, um, both what we'll get paid for.

42

:

During this year and then

in future years as well.

43

:

Um, so yeah, that's kind of

the, the really paired down, uh,

44

:

version of, of what I'm doing

in a kind of complicated space.

45

:

But, um, yeah.

46

:

Okay, sweet.

47

:

That's awesome.

48

:

So basically, you know, you have

two music degrees, I think you have

49

:

a bachelor's and a master's degree.

50

:

And now I think your official

title, is it a financial analyst?

51

:

Is that what it is?

52

:

Yes.

53

:

Yeah.

54

:

Um, so I, it's two

bachelor's degrees actually.

55

:

I, um, my first one is in just kind

of general music, and then my music

56

:

therapy degree is another bachelor's.

57

:

Um, but, uh, yeah.

58

:

So even less impressive, right?

59

:

Well, I mean, that's perfect.

60

:

So, so two different music degrees, a

music degree and a music therapy degree.

61

:

Mm-hmm.

62

:

You were working as a music therapist and

now you're able to work as a financial

63

:

analyst for a Fortune 50 company.

64

:

You know, solving problems when it comes

to healthcare billing, it sounds like.

65

:

Mm-hmm.

66

:

Yes.

67

:

Correct.

68

:

That's awesome.

69

:

That, and that's the journey that's

a little foreshadowing of what

70

:

we're gonna be talking about today.

71

:

So we're gonna get into what your

background is and, and how you

72

:

got to where you're at today.

73

:

Um, but also it does look like,

I mean, I'm no expert, you know,

74

:

I don't work for Humana, but I'm

guessing that your background back

75

:

there is not the Humana offices.

76

:

So can you tell us a

little bit, are you remote?

77

:

Are you hybrid?

78

:

Are you in the office right now?

79

:

Uh, I'm not in the office.

80

:

I'm in my office.

81

:

Um, at home I am, I'm a hybrid employee,

so I do have one office day per week.

82

:

Um, Humana is like headquartered

in Louisville where I'm from.

83

:

Um, and so my team meets in the

office on Wednesdays and, um, which

84

:

works for me really well since

I am a very extroverted person.

85

:

Um, but the rest of the

time I am at home remote.

86

:

Um, it's actually rare that I'm.

87

:

In my office area instead of on the couch.

88

:

So that, that's awesome.

89

:

Um, and I'm guessing that was not the

case as a music therapist, am I right?

90

:

Uh, it was not, no.

91

:

I spent, um, every day, even through the

pandemic, um, every day at the hospital,

92

:

spending most of my time in patient's

rooms, um, sitting with them and, and

93

:

providing music and, um, you know,

going through that therapeutic process.

94

:

Um, so a remote job was, uh.

95

:

A very big change for me.

96

:

Okay.

97

:

And, and how has it been?

98

:

I, I know you mentioned that you're

extrovert is, are you lonely at home?

99

:

Is it is, do you get enough interface?

100

:

Do you get enough support from your team?

101

:

Yeah, I'm really, really lucky.

102

:

My team is super, super supportive.

103

:

Um, we use Microsoft Teams,

so I, I am my boss constantly.

104

:

Um, you know, whether she likes it

or not, but, um, I, I do feel like

105

:

I get enough kind of interaction

and, um, I really love my team.

106

:

And getting to see them on Wednesdays,

but it's also really nice to just kind

107

:

of be relaxed at home while I'm, you

know, working on, um, on my analysis and

108

:

on, you know, all of my, my daily tasks.

109

:

Um, and it, it feels.

110

:

It feels very like, right.

111

:

The pace is still good.

112

:

I'm still, you know, kind of challenged

every day, but it's much different

113

:

than, um, you know, having to like,

go into the hospital and, and kind

114

:

of be part of that crazy environment.

115

:

That's awesome.

116

:

I I love hearing that because I love

that you're like, yeah, I'm, I'm in

117

:

my o my own office today, but to be

honest, my real home office is my couch.

118

:

I think that's awesome.

119

:

Um, that you have the opportunity, you

know, the commute in the morning from the

120

:

bedroom to the couch must be very mm-hmm.

121

:

You know.

122

:

Full of traffic and stuff like that.

123

:

Uh, but, but you know, all jokes aside,

you had to deal with like a commute.

124

:

You had to deal with traffic

in your last, last job.

125

:

Right?

126

:

That was a, a decent amount of driving.

127

:

Yeah, I, I'm very lucky that I live close

to the hospital, um, where I was working.

128

:

But yeah, I mean, it's, I still had to

get on the interstate, um, and, you know.

129

:

Make my way.

130

:

Um, sometimes traffic was worse

than others, but it's, yeah.

131

:

I, uh, I much prefer when my dog is

the only one that's in my way trying

132

:

to, trying to get to the office now.

133

:

Yeah.

134

:

That, that is awesome.

135

:

Um, I also have a dog and I can

testify of the power of having

136

:

your, your dog as your coworker.

137

:

It is like so much fun.

138

:

Mm-hmm.

139

:

Um, and, and now, I mean, one of the

things that you probably couldn't do as

140

:

easily when you were doing the hospital

visits is like, for instance, oh.

141

:

Let's take, let's take the dog out

for a walk or you know, I got to

142

:

feed the dog or I gotta take the

dog outside, or something like that.

143

:

So I imagine that's gotten a lot easier

since you've been able to work remotely.

144

:

Yes.

145

:

Yeah, basil, my dog is, uh,

she is, her quality of life has

146

:

increased even more than mine.

147

:

So that's awesome.

148

:

And that's what matters most, right?

149

:

We don't, we don't really care about

our own lives, it's just about our Ps.

150

:

Exactly.

151

:

Yep.

152

:

Exactly.

153

:

Okay.

154

:

Awesome.

155

:

Um, and you mentioned that you're

able to, I am your boss, and

156

:

that communication's going well.

157

:

'cause one of the questions I get

is, you know, I want a remote job,

158

:

but I'm also new to this field.

159

:

And I'm kind of nervous that like, I'm

not gonna be able to get enough training

160

:

or get enough support from my team.

161

:

You felt like that's been

pretty good at Humana then?

162

:

Yes.

163

:

Yeah.

164

:

Um, my boss is a really,

really wonderful mentor.

165

:

Um, and.

166

:

The, the kind of professional and

personal development that, um, my

167

:

company invests in, um, has been

a really, really good support.

168

:

Um, there are lots of like modules

and things that are provided just

169

:

like by default from the company.

170

:

Um, but then also my boss has been

really wonderful and, you know, we'll

171

:

hop on a Zoom and I'll share my screen

and, you know, I'll say like this,

172

:

I think this is what's giving me a

problem, but, um, I can't, you know,

173

:

figure out what I need to change or.

174

:

What does, what does this actually mean?

175

:

Um, and she can tell me and she'll

kind of help me puzzle through it and,

176

:

and figure out, um, you know, where I

went wrong or how I should approach it

177

:

in the future or what, what to tweak.

178

:

Um, and so that's really, really helpful.

179

:

That's awesome.

180

:

So you not only have, like your boss,

you're able to, you know, message

181

:

anytime you get stuck, but you also

have some sort of provided learning

182

:

so that you're not like, stuck with

the skills that you're at right now.

183

:

You can kind of upskill as you

go, it sounds like as well, right?

184

:

Mm-hmm.

185

:

Exactly.

186

:

Yes.

187

:

Yeah, my, uh, my next thing to tackle

is, um, getting into some python for like

188

:

moving data from one place to another.

189

:

So, um, I'm excited to get started

on that in the next couple of weeks.

190

:

Sweet.

191

:

That's awesome.

192

:

Very cool.

193

:

Um, okay, awesome.

194

:

So actually, wh while, while

you've mentioned Python mm-hmm.

195

:

Let's talk about, as you know, an entry

level financial analyst new to the field.

196

:

What type of, what type of tools

are you using on a day-to-day basis?

197

:

Yeah, so biggest one is sql.

198

:

Um, we use SQL Server.

199

:

Um.

200

:

And kind of the whole, like

Microsoft Suite, all of that.

201

:

Um, lots of excel for the kind

of like financial part of it.

202

:

Um, but most of my analysis

and most of the testing that

203

:

we're doing is within sql.

204

:

Um, and yeah, that's been, it's

been really fun to kind of take,

205

:

uh, the skills that I know like.

206

:

Uh, just in my own little like, simple

projects into, you know, actual like

207

:

millions and millions of rows of data.

208

:

Um, and, you know, see,

see how it translates.

209

:

Yeah.

210

:

I'm sure some of it is very similar, like,

like you kind of have the base for it,

211

:

but it's probably like you're doing things

you might not have necessarily expected.

212

:

Um, and using things kind of in a new

way with his, with his new application.

213

:

Mm-hmm.

214

:

Yes.

215

:

Yeah.

216

:

There and there's a lot

of, um, kind of logical.

217

:

Like analytical thinking.

218

:

Um, and you know, that's part

of the learning curve of, of.

219

:

Going into, you know, this specific

industry, um, like healthcare.

220

:

I thought, you know, being in the

hospital every day, I thought I knew

221

:

all of the acronyms, um, that came

with like the medical, you know, field.

222

:

Um, but apparently I didn't.

223

:

Health insurance is

like totally different.

224

:

So, um, yeah, lots of acronyms.

225

:

Um, lots of kind of the, the

logical analytical thinking to get

226

:

from point A to point B and then

figure out how to get there in sql.

227

:

Okay.

228

:

I love that.

229

:

And that's something that we

didn't necessarily talk about.

230

:

We, we, I mean, we mentioned

your background, we

231

:

mentioned your music degrees.

232

:

We, we said the term music

therapy a couple times.

233

:

I wasn't familiar with

music therapy beforehand.

234

:

So, um, maybe, if you don't mind,

will you just give like a, a quick

235

:

introduction to what you were doing?

236

:

You kind of mentioned it

earlier, but if I was, if I was a

237

:

5-year-old, what is music therapy?

238

:

Sure.

239

:

So, um, you know, the go-to line, I

guess, is that music therapy is using

240

:

music to accomplish non-musical goals.

241

:

So, um, in the hospital, what I was

doing most of the time was using music

242

:

for decreasing pain, decreasing anxiety,

um, kind of providing that additional

243

:

emotional support, um, that people often

don't get, um, especially when they're

244

:

going through something that is, you know.

245

:

Potentially like traumatic and scary

for them, like being in the hospital.

246

:

Um, and you know, we worked

really closely with our like

247

:

hospice and palliative care team.

248

:

Um, so a lot of, uh, folks

who were going through kind of

249

:

the end of life process, um.

250

:

And Yeah, that's kind of what

my, my daily life was like.

251

:

Yeah.

252

:

And, and I think that's important to

realize because one of the tips that

253

:

we, that we talk about throughout

the data analytics accelerator is,

254

:

can we find you a stepping stone job?

255

:

Right?

256

:

Because you're new to this

world of, of data, right?

257

:

You're, you're new to this world of data.

258

:

You had no prior, you know, math

jobs or science jobs, right?

259

:

It was, it was the music stuff, right?

260

:

Um, but you were able to land this.

261

:

This financial analyst

role pretty quickly, like

262

:

within, within about 90 days.

263

:

I was looking, I was trying to look, find

our exact, when you told me you had the

264

:

interview and you had the offer, um, and

when you joined, you joined like right

265

:

before Christmas, and then I think you

started working like mid-March, right?

266

:

Mm-hmm.

267

:

Yes.

268

:

Yeah.

269

:

Um, so I, I like, you know, signed up,

um, clicked submit or whatever on the.

270

:

Accelerator package, like

right before Christmas.

271

:

Um, started actually like doing the

program right after Christmas, like the

272

:

week before Christmas and New Year's.

273

:

Um, and I, I think my job.

274

:

The interview was on March 1st, um,

which was a Wednesday or whatever

275

:

the Wednesday was that week.

276

:

And then that Friday I accepted my offer.

277

:

Um, so yeah, I was,

uh, not expecting that.

278

:

Um.

279

:

That's not even, that's not even 60 days.

280

:

'cause February is not even 30 days.

281

:

Right.

282

:

So that's basically Right.

283

:

Yeah.

284

:

So that's awesome.

285

:

Um, and absolutely incredible.

286

:

Congratulations.

287

:

Thank you.

288

:

I cut you off.

289

:

Thank you.

290

:

Keep, keep talk, talking us

through that, through that journey.

291

:

Yeah.

292

:

So, um, I should back up and say that part

of what I was doing, um, before kind of

293

:

getting into the, into the accelerator

bootcamp, um, you know, when I.

294

:

Was looking into data analytics as

a potential, you know, career move.

295

:

Um, I did kind of what anybody does and

just Googled it, um, and landed on the

296

:

Google, the Coursera, like Google mm-hmm.

297

:

Data analytics program.

298

:

Mm-hmm.

299

:

Um, and I was doing that for a while.

300

:

I think I started that

sometime in the summer.

301

:

Um, last year.

302

:

Felt, um, like I was understanding things.

303

:

Um, I didn't.

304

:

I didn't have any, you know,

foundational knowledge besides

305

:

like, using Excel for budgeting.

306

:

Um, and you know, I think it was a really

good introduction into like, what is data

307

:

analytics and all of that sort of thing.

308

:

But I didn't, um, I made it like

three quarters of the way through,

309

:

but I didn't feel like I could like

actually apply my knowledge in a

310

:

way that was, um, helpful for me.

311

:

I was like understanding it as I was going

through, but there wasn't a lot of like.

312

:

There weren't any steps after that.

313

:

So, um, I was looking for something

that was just more hands-on

314

:

and more like active for me.

315

:

Um, that's how I tend to learn best.

316

:

And so I was, you know, just kind of

looking to see what was out there.

317

:

And, um, I think, I think you had

a sale going on, I saw on LinkedIn

318

:

and I was like, that sounds good.

319

:

Um, you know, most boot camps are

like five grand plus, and you know,

320

:

that's not something that in my.

321

:

Previous job that I could even consider

budgeting for, um, in any kind of,

322

:

you know, uh, reasonable timeline

for wanting to make a career move.

323

:

So, um, I was like, sounds great.

324

:

This guy's cool.

325

:

I'm gonna just do this

and see where it goes.

326

:

And so from there, that's kind of

when I, uh, started like doing.

327

:

Doing the Analytics Accelerator

Bootcamp, um, and the curriculum,

328

:

and I think it, that is what really.

329

:

Made a big difference for me.

330

:

Yeah.

331

:

I, I think, I think your story

is, you know, very similar.

332

:

In fact, someone emailed me today and

said, you know, how is your program

333

:

different than the Google data cert?

334

:

Um, which is, which is a

common question, um mm-hmm.

335

:

And I think, I think you kind of

nailed it, like actually applying

336

:

what we're, what you've learned.

337

:

Right.

338

:

Um, and then really focusing on creating

the projects and the networking.

339

:

Right.

340

:

Because mm-hmm.

341

:

At the end of the day, if you don't

have the projects, you don't have the

342

:

network, it's a lot harder to land

that job and then also just doing it.

343

:

Mm-hmm.

344

:

With someone, like someone that's

able to, you know, talk to you.

345

:

I know you were pretty active on our

community, so having all the peers

346

:

around you, uh, I think, I think that's

pretty helpful for, for most people.

347

:

Um, and the other thing you

did really well is, and I mean,

348

:

I, I think this was helpful.

349

:

You can tell me if I, if I'm wrong, um,

but you were trying to land a data job.

350

:

You don't have necessarily the,

what people would consider the

351

:

traditional or the ideal background.

352

:

I don't think there is a traditional

or ideal background for data analytics,

353

:

but that's, that's besides the point.

354

:

Um, but you found this job inside of

healthcare and you have been working

355

:

in healthcare as this music therapist.

356

:

You've been visiting hospitals, like you

said, you know, hospitals speak a little

357

:

bit like the acronyms and stuff like that.

358

:

Did that play a role in

helping you land this job?

359

:

Like, was that helpful to

know the hospital stuff?

360

:

Yeah, I think so.

361

:

Um, you know, especially during

my interview process, that was

362

:

something that I spoke to a lot.

363

:

Um, you know, and having kind of that

background knowledge of just how the

364

:

industry works, um, and understanding

like, yeah, I might not know like the

365

:

backend of health insurance, but I

know like what these things mean and

366

:

I know, you know, kind of why things

are set up the way that they are.

367

:

Um, even if, I dunno the details of like.

368

:

How, how it works on the backend.

369

:

Um, and one of the projects I think that

really helped me kind of be able to speak

370

:

to that was the SQL project, um, and the

accelerator, the, um, healthcare analysis.

371

:

That was something that I talked about

in all of the interviews that I had.

372

:

Um, and they were really, really

interested to know, you know, not

373

:

only to see that I had some SQL

skills, but also just to see like.

374

:

I had used my prior knowledge and

like, um, how I had applied that

375

:

understanding of the industry

to the analysis, like with sql.

376

:

Um, so that I think was

really, really helpful for me.

377

:

Um.

378

:

Yeah, in that whole interview process,

gosh, I actually, I mean, I should have

379

:

realized that, but I didn't even, I

didn't even realize that, and that's so

380

:

cool because they were like, Hey, we're

hiring for a financial data analyst role.

381

:

The the hope is that someone

will understand data analytics,

382

:

they'll understand sql.

383

:

They'll, they'll understand

hospital, or I guess healthcare data.

384

:

And you were like, oh, well here's a

project I've done that you can read

385

:

where I analyzed, I can't remember

how much data is in that one, like 1.6

386

:

million rows of hospital data.

387

:

Mm-hmm.

388

:

And like looked at outcomes and

like looked at like what procedures

389

:

led to these different things

and how race played in role in

390

:

the hospital and stuff like that.

391

:

And you're like, just, here you go.

392

:

This is, this is my evidence.

393

:

Right.

394

:

Are you interested, Uhhuh?

395

:

That must have been really

powerful for the recruiter.

396

:

They're like, oh.

397

:

Wow.

398

:

Uh, SQL project with healthcare data.

399

:

I'm, I'm sure they didn't have

very many other projects like that.

400

:

If I were to guess, I don't know.

401

:

But if I were to guess, I don't

know who else applied, but

402

:

apparently I did something right.

403

:

So, yeah.

404

:

'cause, 'cause you interviewed and then

like three days later had an offer.

405

:

Mm-hmm.

406

:

Yeah.

407

:

That's amazing con that's so amazing.

408

:

Congrats.

409

:

Thank you.

410

:

Um, one, one of the things I just wanna,

I wanna highlight, um, that makes me

411

:

so happy to hear, because when I was

designing the, the analytics accelerator,

412

:

I was like, okay, we have to do projects.

413

:

And to be perfectly honest, uh,

when I first got into helping people

414

:

land data jobs, I, I had the same

philosophy that projects were the way.

415

:

But I had a little bit of a

different twist where I was

416

:

like, projects should be fun.

417

:

It's always fun.

418

:

To do your own personal data.

419

:

So when I originally launched my

bootcamp, all of the projects were

420

:

actually from your own life, like

your own screen time on your phone,

421

:

the data, the, the music you listen

to, you know, and stuff like that.

422

:

And that those projects were really fun

and I think they were very impressive

423

:

to recruiters and hiring managers.

424

:

They were a little bit harder because it's

just hard, keep getting your own data.

425

:

But now that we've transitioned to.

426

:

Using data from all the

different industries.

427

:

I'm so happy to hear that we, when

I was choosing the nine industries

428

:

for the nine projects, I was like,

man, there's so many industries.

429

:

Which ones did we choose?

430

:

And I'm so glad to hear that the

healthcare and the SQL combo was

431

:

at least useful for one person.

432

:

That's so good to hear.

433

:

Yes, yes, for sure.

434

:

Um, and actually I think just

having the projects in general

435

:

and having the specific, um.

436

:

Like specific tools for a

specific project, um, I think

437

:

was really, really helpful.

438

:

Um, and, you know, maybe

just also to highlight, uh,

439

:

another aspect of the bootcamp.

440

:

Um, I think the difference for me, I

was applying to things, um, kind of,

441

:

you know, throughout the whole, uh.

442

:

The time that I was, you

know, doing all the modules.

443

:

Um, and I wasn't really getting

a lot of bites and, you know,

444

:

kind of trying to network and,

and get referrals for, for jobs.

445

:

But, um, I think the thing that made

the difference was having, I went

446

:

to one of your, um, I don't remember

if it was a live session or just a

447

:

module, but, um, all about resumes

and like optimizing your resume.

448

:

Um, and so I added like.

449

:

Literally, as I was watching, I

was like, okay, I'm gonna add these

450

:

links to my portfolio projects.

451

:

I'm gonna add, you know, a blurb about

what I learned, what I analyzed, what

452

:

I, and why, um, and what I found.

453

:

Um, and I like sent off a round of,

of applications kind of with that new

454

:

resume, with my projects added like

an actual section, not just a link

455

:

to my, um, to my portfolio site and.

456

:

I like literally had three interviews

lined up for like that same week.

457

:

Wow.

458

:

From just that difference.

459

:

Um, and that was, you know, one of the,

one of those interviews that I had is

460

:

the role that I ended up accepting.

461

:

So, and yeah.

462

:

Did you, did you apply to that

job or did, did they find you?

463

:

So I applied for it.

464

:

Um, I have, uh, I know several people that

also work for Humana and I had someone

465

:

who was willing to let me be a, um.

466

:

Or be, you know, my referral.

467

:

Um, so definitely worked kind of with my

network and, and connecting with people,

468

:

um, to get my in, um, Humana as a company

that I have, you know, uh, considered

469

:

working for, for, for a long time.

470

:

Um, and you know, I know just

from having those personal, uh,

471

:

relationships with people here, um.

472

:

They're, they treat their

employees really well.

473

:

And so I was like, oh yeah, that's

like a company I really wanna work for.

474

:

So, um, that's kind of how I was

focusing my, my networking attention.

475

:

Um, but yeah, I had very, very quick

turnaround from submitting those

476

:

applications to hearing from recruiters

for the, the specific positions.

477

:

Okay.

478

:

There's a lot there I wanna unpack.

479

:

Um, number one, did you apply on like

LinkedIn jobs Indeed, or on their website?

480

:

On their website.

481

:

Um, so I found them on LinkedIn,

but I went to the website to apply.

482

:

Okay.

483

:

Um, yeah.

484

:

Okay.

485

:

Two.

486

:

Um, one of the things I wanna, I wanna

highlight here is, um, I don't know if

487

:

you remember this, but the job, the job

description, it probably said hybrid

488

:

on the job description, do you think?

489

:

Mm-hmm.

490

:

Or do you say in mm-hmm.

491

:

Okay.

492

:

And I wanna highlight that because I've,

no, this is like a super underrated play

493

:

that everyone is sleeping on right now.

494

:

And that's the idea of hybrid jobs.

495

:

Mm-hmm.

496

:

Everyone is like, oh, I

don't wanna be in person.

497

:

Right.

498

:

So they, they go and they go

to LinkedIn jobs, they use

499

:

the Boolean search for remote.

500

:

Mm-hmm.

501

:

And they're competing with literally

thousands of other people for these

502

:

remote jobs, because literally you

can be all over the US or the world.

503

:

Right.

504

:

And be an applicant for this job.

505

:

Mm-hmm.

506

:

But like your role, you're in the office.

507

:

Like what?

508

:

Eight hours a week on Wednesday.

509

:

Mm-hmm.

510

:

Like, if you want to like, you know, work

from home, from, you know, the rest of the

511

:

days, you can, if you wanna, I don't know

Humana's exact policy, but let's just say

512

:

you wanna go visit your, your parents,

or I don't know, your brother, right.

513

:

You could, you could go, mm-hmm.

514

:

You could leave Wednesday night and

come back home, you know, Tuesday night.

515

:

Like that's like a week that you could

be working somewhere else, like you're.

516

:

Not quite remote, but

you're 90% there, right?

517

:

I guess.

518

:

I guess literally 75%, right?

519

:

Or what, what, what?

520

:

80% there.

521

:

Um, yeah.

522

:

80.

523

:

Yes.

524

:

But, but it's, but it's

pretty good, right?

525

:

Mm-hmm.

526

:

Yeah.

527

:

And, and like I said, I am a really

extroverted person, so I really

528

:

like, you know, I, I think we get

less done on Wednesdays than we

529

:

do, like when we're all remote.

530

:

Um, you know, 'cause we're.

531

:

Catching up with each other and, uh,

you know, socializing a little bit.

532

:

Um, but yeah, we have, my team

has a lot of freedom outside of

533

:

those, those, uh, in-person days.

534

:

And, you know, if you do need to take

a, a remote day, that's also fine.

535

:

Um, you know, I had a coworker

yesterday who was like, yeah, I just.

536

:

I'm not feeling super well,

not well enough to not work,

537

:

but can I just stay home today?

538

:

And my team was like, yeah, of course.

539

:

Just call into the meeting

that we have and we'll be fine.

540

:

Um, so there's a lot of flexibility there.

541

:

That's, and that's awesome.

542

:

And I think people are like,

no, I only want a remote job.

543

:

But the hard thing is like when

you're doing a remote job, you're

544

:

competing with people you know,

not only in Louisville, right?

545

:

You're competing with people all over

the country, but if you're hybrid mm-hmm.

546

:

That job pool that they're selecting from

the candidate pool is so much smaller.

547

:

And so you can stand out so

much more as a candidate.

548

:

Um, the third thing I wanna mention is,

you know, you mentioned the referral.

549

:

Mm-hmm.

550

:

And people are gonna be like,

well, okay, I don't know anyone.

551

:

You know, I, no one's gonna refer me, but

the people that referred you, what, what

552

:

part of the company do they work for?

553

:

Uh, not mine.

554

:

Um, yeah, it's, uh, there are several

organizations kind of within Humana.

555

:

Um, and they are in one that

is parallel with mine, but

556

:

they are not in finance at all.

557

:

Um, and so, you know.

558

:

They, I even asked her, she, she like,

looked into some of the jobs when I was

559

:

talking with her and she was like, yeah,

I don't know these hiring managers.

560

:

Um, but I know this person who, um, you

know, worked with this other person and,

561

:

you know, she kind of connected some

dots, but she, I didn't know, she didn't

562

:

know anyone personally who was like, in

charge of hiring or, you know, the next

563

:

like three steps up, um, from my manager.

564

:

So, um.

565

:

Yeah, I think it's a powerful thing

to, even if you aren't, if you can get

566

:

a referral from someone, um, even if

they aren't directly involved with.

567

:

The position that you're applying

for, I think it's really, really

568

:

worth it to try to, you know, still

build those relationships and, um,

569

:

and see if they can help you out.

570

:

Yeah, a hundred percent.

571

:

Like when I'm working with a lot

of people, they're like, Avery, I

572

:

don't know anyone to get referrals.

573

:

And the answer to that is bull crap.

574

:

Unless you're like your brand new

to the country and you've never,

575

:

like, you don't speak English, or

like you haven't really met people.

576

:

Like, you at least know

someone who works somewhere.

577

:

Mm-hmm.

578

:

And sometimes, mm-hmm.

579

:

Sometimes, sometimes that person's

gonna work at like, as a grocer at

580

:

like, at like Smith's family grocer

and like, that's not gonna be useful.

581

:

But like you've probably have at least,

you know, 20 contacts in your phone.

582

:

Like open up your phone and go through

one by one and just be like, okay,

583

:

Paul Adams, where does he work?

584

:

Alejandra und, where does he work?

585

:

Paul Alstrom, where does he work?

586

:

You know, and think through.

587

:

Do these people work for a company that

have an opening for a data analyst?

588

:

Yes or no?

589

:

Mm-hmm.

590

:

And if they do, it doesn't matter if

they're in marketing or if they're

591

:

in sales, or if they're, you know,

really doesn't really matter because

592

:

the company just wants to kind of.

593

:

To hire good people.

594

:

And if that person's at that

company, that's probably because they

595

:

think that person's a good person.

596

:

Mm-hmm.

597

:

And so if that person has a friend,

that's probably also another good person.

598

:

And so just having any sort of

referral from any company employee,

599

:

I think is worth exploring.

600

:

And I think it gives you a

leg up in the application.

601

:

So I think a job well done from you,

because you went for the hybrid, you

602

:

went for the referral, and I mean,

that's what allows you to, you know,

603

:

do an interview and then bam, you

have an offer like two days later.

604

:

Yeah, it was, uh, it, it wasn't a

short process, you know, from, uh,

605

:

starting getting into data at all to,

um, you know, accepting a job offer.

606

:

But I think, um, the, the, the steps

that I took in the last, you know,

607

:

couple of months of that journey, um,

really, really made the difference.

608

:

And, um.

609

:

Yeah, a lot of it was kind of

prompted by the accelerator

610

:

program, so thank you for that.

611

:

Yeah, of course.

612

:

We're, I'm so glad it

it worked out for you.

613

:

Mm-hmm.

614

:

Um, okay.

615

:

Before we let you go, I gotta ask you a

few more questions about the interview.

616

:

Sure.

617

:

Was it, was it technical?

618

:

No.

619

:

Um.

620

:

Uh, and maybe part of it was because I

had projects to kind of show what I knew.

621

:

Um, but we didn't, there wasn't like an

assessment for me, um, for any of the

622

:

jobs that I interviewed for, you know,

kind of in that round of interviewing.

623

:

Um, I talked about my projects a lot.

624

:

They ask questions about the projects

themselves and kind of specifically what

625

:

learned like the projects you had done.

626

:

Learned.

627

:

Yes.

628

:

Yeah.

629

:

So, um, the, the healthcare

one, um, I talked about.

630

:

Um, oh, I forget which is which now.

631

:

But, um, I talked about the, I

think Massachusetts education one.

632

:

Yeah.

633

:

Uhhuh.

634

:

Um, I talked about that one.

635

:

I talked a little bit about

the data visualization one

636

:

that I had on my portfolio.

637

:

But, um, yeah, I like, they would ask me

specific questions about, you know, like.

638

:

What was your process with this?

639

:

What did you know?

640

:

How did you come to this conclusion

based on this data and, um, things

641

:

like that rather than like, you

know, here is a, a data set.

642

:

Can you query this?

643

:

Like, I didn't have to do any of that.

644

:

Like really, really technical stuff.

645

:

I think because they could see that I

knew, you know, how to at least do it.

646

:

Select from where statement, and then they

could ask me those deeper level questions.

647

:

Um, yeah.

648

:

Based on my portfolio, I think that's so

powerful because one of the things we talk

649

:

about in DAA is that a lot of times the

people interviewing you are busy people

650

:

and they don't wanna be interviewing you.

651

:

And so they're coming in with

questions five minutes before

652

:

they're actually doing the interview.

653

:

That's not true of everyone, but a lot

of the times I've, I've hired people

654

:

and I know that I've done that before.

655

:

Mm-hmm.

656

:

And so sometimes if

you give them projects.

657

:

All of a sudden you just gave them

material for them to ask you questions

658

:

about, and you kind of flipped the

interview where you're, you've almost made

659

:

the interview about stuff that you know

and stuff that you've done versus them

660

:

just like randomly asking you questions.

661

:

Um, which I think is really, it

makes it way less nerve wracking and

662

:

it makes you look more impressive.

663

:

So I think, I think that's mm-hmm.

664

:

A, a win-win.

665

:

So overall, you felt prepared and

it was just the, the one interview.

666

:

Uh, yes.

667

:

So for the role that I had, um, it, it

was in person, um, which was helpful

668

:

for me, um, because I, I tend to do

really well when I'm talking to people

669

:

and, um, feel less nervous than, you

know, if I'm, um, if it's like a phone

670

:

interview or something like that.

671

:

Um, but we did, it was one.

672

:

Day.

673

:

Um, but interviews with

several people on the team.

674

:

Um, but we had really similar

conversations kind of between that,

675

:

um, as pertains to kind of their

role and, and the difference between

676

:

the role that they're hiring for.

677

:

Um, but yeah, I felt really prepared.

678

:

I felt, um, like I knew what I was

talking about, kind of going in.

679

:

I obviously had done these whole

projects and could speak on them.

680

:

Um, and so that made me

feel really confident in.

681

:

My skills and also in my like,

you know, presence and, and being

682

:

able to really engage with them.

683

:

Um, instead of being worried about,

you know, am I gonna remember how

684

:

to, like what the syntax is for

this, you know, specific thing

685

:

that they're gonna ask me about.

686

:

Yeah.

687

:

That's, that's awesome.

688

:

Um, I love that the

projects brings confidence.

689

:

That's an important takeaway.

690

:

Mm-hmm.

691

:

Um, yeah.

692

:

Okay.

693

:

And then, uh, we did have a question here.

694

:

Um, you can answer this to your heart's

content, um, as much as, as you do or not.

695

:

Um, but the question is, did you feel

the need to negotiate or were you

696

:

pretty happy, uh, with your offer?

697

:

So, um.

698

:

As I mentioned, I had interviews

for three different roles, um, kind

699

:

of, you know, all at the same time.

700

:

Um, it was that like last round

of applications that I sent

701

:

in after changing my resume.

702

:

Um, had all those interviews within, you

know, that same week, the, um, the ones

703

:

on that Wednesday where the last ones.

704

:

Um, and a, the recruiter contacted

me, um, and actually said that I had.

705

:

Um, gotten offers from all three and

that they wanted to, that they wanted

706

:

to, um, you know, see what was my

preference and that sort of thing.

707

:

And I didn't negotiate with numbers

necessarily, but I said that a, um,

708

:

salary would put play a, a part in

my decision of which role to take.

709

:

Um, and so I asked if they could give

me, you know, a range for each one.

710

:

Um, so they came back with that and, um.

711

:

You know, told me the ranges of what,

what they could offer for each role.

712

:

Um, and then I was really happy that

the, the one that I had wanted the

713

:

most did actually have, you know, the

highest offer as well, the highest range.

714

:

Um, and so I, you know,

happily took that one.

715

:

Um, so I didn't have to

necessarily negotiate.

716

:

Um, and then when I like

accepted that offer, they.

717

:

Um, said it was gonna be the, the highest

end of the, of the range they'd given me.

718

:

They just gave me that top number.

719

:

Um, so you got what?

720

:

You got what you wanted?

721

:

Exactly.

722

:

Yeah.

723

:

I didn't have to like,

you know, negotiate like.

724

:

Face-to-face with somebody, but, um,

you know, letting them know that that

725

:

was an important part of my decision.

726

:

I, I think that's good.

727

:

Um, we, you know, a lot of people will

talk about negotiating, um, and I think

728

:

I'm probably not the, the best teacher

of negotiation, if I'm being honest.

729

:

I've never really negotiated that

much, but so many students in

730

:

our program have just been so.

731

:

Happy with the offer that they get,

that, that, I mean, negotiating

732

:

is always probably a good idea.

733

:

Uh, but anyways, a lot of people

have just been super happy that

734

:

they're like, I'll take it.

735

:

I'm so, so stoked with this.

736

:

Right?

737

:

If someone offered me $10

million right now to go work

738

:

for them, I'm not negotiating.

739

:

I'm taking the 10 million

million dollars right.

740

:

And, and I mean, uh, kind

of the same idea there.

741

:

Um, mm-hmm.

742

:

Okay.

743

:

So one with this, uh, any advice that

you'd like to give to people with

744

:

non-traditional backgrounds, people

with, um, maybe music backgrounds?

745

:

What, what would you say and, and

that helped you in your journey?

746

:

Or what, what advice would you give them?

747

:

Yeah.

748

:

Um, so number one piece of like

actionable advice is to do projects.

749

:

Um, do projects that are based on

skills that you have or, you know,

750

:

the industry that you have, and then

also ones that, um, show that you

751

:

have knowledge for where you wanna go.

752

:

Um, so if it's healthcare, if

it's, um, you know, marketing, like

753

:

whatever you're trying to kind of.

754

:

Break into, do projects with that

show that you know how to use the

755

:

technical skills, um, in that industry.

756

:

Um, and then just in general, I think,

um, something that I realized through

757

:

my journey was that even if you are

like just starting and you don't really

758

:

have a whole lot of like foundational

knowledge, um, to go off of, you are.

759

:

Um, more capable and you know, a

lot more than you think that you do.

760

:

Um, you know, everything

transfers to everything else.

761

:

Um, I guarantee that there's

something that you, like do in your

762

:

daily job that relates to, you know,

your, your data analytics learning.

763

:

Um, and I think that if you have started

on this journey and you know, are, um.

764

:

Even if you are at the beginning,

you've done the hard part of like

765

:

making the decision and starting.

766

:

Um, and so now it's just about consistency

and you know, keeping that going.

767

:

I, I love that.

768

:

I hope you guys listening

take that to heart.

769

:

Keep in mind that was a music

therapist telling you that you have

770

:

something in your current job that

is relatable to data analytics.

771

:

If you asked me like the most opposite

of a data analytics job ever, I might

772

:

say a music therapist, but you're

absolutely right Aaron, that no matter

773

:

what you're doing, you can relate

something to what you're currently doing.

774

:

It is experience for a data analyst job.

775

:

So, you know, don't be discouraged

when you see, you know, one

776

:

to two years of experience.

777

:

Two to five years of experience.

778

:

You have some sort of experience

that you can draw and I loved the

779

:

advice, uh, on doing projects.

780

:

So, uh, Aaron, thanks so

much for being on the show.

781

:

Uh, we'll have your LinkedIn down

below in the show notes that people

782

:

can connect with you and, uh, just

so excited for you and your journey.

783

:

Aaron, thanks for sharing

it with all of us here.

784

:

Thanks so much for having me.

785

:

Yeah, no problem.

786

:

Um, okay, great.

787

:

Thanks everyone for listening.

788

:

If you guys are listening live

on YouTube or LinkedIn, uh, we

789

:

just wanna say hello to you guys.

790

:

Um, also, if you guys did not know,

I'm doing a live version of the data

791

:

analytics accelerator, um, starting

on Monday, and I want you guys to be

792

:

part of that, um, awesome program.

793

:

We're going to be, if you guys are

like, I want some more guidance, I

794

:

want some more community, we're doing.

795

:

Two hour live sessions every Monday.

796

:

And then where I'm going to

be building the projects that

797

:

Aaron talked about, we're gonna

build the SQL Hospital project.

798

:

We're gonna build, uh, the

DoorDash marketing project.

799

:

We're gonna build the education

Tableau project altogether

800

:

on those Monday sessions.

801

:

And then we're doing a live

office hour on Thursday.

802

:

So if you're interested, you can go

to data career jumpstart.com/daa.

803

:

Or you can just send me a DM on LinkedIn

and I'll get you the stuff you need.

804

:

So I just wanna make sure y'all,

you guys know, 'cause that is an

805

:

opportunity that, um, I haven't done

before where I'm actually building

806

:

the projects and I'm going live for

three hours every week with you guys.

807

:

So, uh, hopefully that's,

that's pretty exciting.

808

:

That Great.

809

:

Aaron, anything else?

810

:

No, I don't think so.

811

:

Thanks so much for having me and,

uh, good luck everybody listening.

812

:

Yeah, sounds good.

813

:

All right.

814

:

Bye everyone.

815

:

Let's see.

Follow

Links

Chapters

Video

More from YouTube