Episode 204

full
Published on:

31st Mar 2026

204: She Became a Data Analyst in 67 Days! (No Prior Experience)

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

Transcript
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.

All Episodes Previous Episode

Listen for free

Show artwork for Data Career Podcast: Helping You Land a Data Analyst Job FAST

About the Podcast

Data Career Podcast: Helping You Land a Data Analyst Job FAST
The Data Career Podcast: helping you break into data analytics, build your data career, and develop a personal brand

About your host

Profile picture for Avery Smith

Avery Smith

Avery Smith is the host of The Data Career Podcast & founder of Data Career Jumpstart, an online platform dedicated to helping individuals transition into and advance within the data analytics field. After studying chemical engineering in college, Avery pivoted his career into data, and later earned a Masters in Data Analytics from Georgia Tech. He’s worked as a data analyst, data engineer, and data scientist for companies like Vaporsens, ExxonMobil, Harley Davidson, MIT, and the Utah Jazz. Avery lives in the mountains of Utah where he enjoys running, skiing, & hiking with his wife, dog, and new born baby.