Meet  @SundasKhalid: High school dropout, immigrant, and now a powerhouse in data at Google! She shares pivotal tips for breaking into data, invaluable financial literacy insights, and how she champions salary negotiation by helping others secure higher pay.

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⌚ TIMESTAMPS

00:00 - Introduction

01:05 - From high school dropout, immigrant child, to analytics lead at Google!

15:24 - Number 1 piece of advice

19:36 - AI in the workplace

24:04 - Financial literacy and salary negotiation

🔗 CONNECT WITH SUNDAS

🎥 YouTube Channel: https://www.youtube.com/@SundasKhalid

🤝 LinkedIn: https://www.linkedin.com/in/sundaskhalid/

📸 Instagram: https://www.instagram.com/sundaskhalidd

🎵 TikTok: https://www.tiktok.com/@sundaskhalidd

💻 Website: https://sundaskhalid.com/

🎥 Facebook: https://www.facebook.com/sundaskhalidd/

🔗 CONNECT WITH AVERY

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

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

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If you're breaking into data right now, you've probably seen one of

2

Sundus Khalid's videos with over 250,

000 subscribers on both YouTube and

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Instagram and absolutely killer content.

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She's near impossible to miss.

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She's worked as a data analyst, a

data engineer, and a data scientist.

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At both Amazon and Google.

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But in today's episode, you're

going to hear Sundance's

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story in a whole new light.

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You see, you know Sundance as the rock

star at Google and Amazon that she is.

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But she's actually an immigrant

high school dropout who didn't even

11

speak English until later in life.

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She didn't go to an Ivy League

school, and she even started

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her career later than most.

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She is living proof that it's

never too late to break into

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data, no matter your background.

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So coming up, you'll hear Sundas

number one data skill that you

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need to learn no matter what.

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Sundas Khalid: I would have to pick

a coding language, and it's gonna be

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Avery: s t.

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If she likes being a data analyst, a

data scientist, or a data engineer more.

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I

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Sundas Khalid: don't want to pick.

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I would say like d k is

my favorite for building.

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And

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Avery: her crazy financial journey

and what you can take from it.

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Nobody

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Sundas Khalid: keeps.

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That much money in their bank account.

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Like people invest with

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Avery: that.

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Let's get into the episode.

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Sundance.

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I'm so excited to have you on

because you have such a unique story.

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You're a high school dropout,

immigrant child, and now you're an

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analytics lead at freaking Google.

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So how on earth did you get here?

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Sundas Khalid: First of all,

thank you so much, Avery, for

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having me on your podcast.

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Um, and thanks for a great intro.

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It's a long story, but I think like

you summarize it really, really well.

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I am a high school dropout and I'm

an immigrant and I was six years gap

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between my high school and my university.

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So when I look back now to like 10, 15

years ago, I can't believe that I am here.

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So it's been a long journey, a little

bumpy, but I am really grateful for all

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the support that I've had throughout my.

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career and throughout

my education journey.

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So a TLDR is that I went to University

of Washington, went to business

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school, and in the business school,

I actually learned about data

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analytics, databases, SQL and whatnot.

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And that's where my love and my

passion started for the data field.

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Then I just kept building on top of it.

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I didn't have enough time to graduate

with a CS or a data science degree.

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So I ended up building on my own,

like continuing learning on my own.

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So I'm a self taught data

engineer, data scientist.

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Data analysts, like

whatever you want to call.

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So it's been a long winded journey, but

I'm so happy to be here and I'm happy

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to answer and deep dive into any of

these topics, uh, you'll let me know.

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Avery: Well, I'm super excited because

I think there's a lot of people who

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are watching this, who are like you,

who might be immigrants to the U S who,

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you know, maybe started school a little

bit later or later in their career.

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And they're like, man, I don't

know how the heck I'm going

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to break into data analytics.

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I think you're living proof

that like you can start late.

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You can start disadvantaged.

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Like you didn't even start speaking

English till later in life.

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And you can still end up on the

top, which I think is really cool.

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And also you didn't go to

like a brand name university.

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You didn't study computer science.

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You didn't study math.

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You kind of just studied business.

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Uh, what's been like the, the biggest

thing for you in your career journey?

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That's allowed you to, to

get to where you're at.

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Sundas Khalid: Um, so I think like

a couple of things that helped me

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really daily, uh, in my career.

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One is.

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Knowing what I want to do and

when I don't know what I want

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to do, like I still kept going.

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So when I started in my career, like my

first internship, what am I was at Amazon?

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Um, I was lucky enough

to get that internship.

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It was really coincidental

because I learned about that

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internship at a networking event

while I was going to school.

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Prior to that, I was getting

rejected from all the internships.

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From my experience, like I have

always been open to trying new things.

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And Amazon is something that I

didn't want to try initially,

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but I just jumped into it.

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One of my best friends at that time,

um, he actually worked at Amazon and

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he was like, no, you have two kids.

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There's no way you're ever

going to survive at Amazon.

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I was like, no, I have to try it

for myself and I have to go for it.

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I ended up going for it.

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And that was ended up being one

of the best career decisions that

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I've made because one, Amazon

took a lot of chances on me.

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Like it let me try out

new things, for example.

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My first job was a data engineer,

uh, which I like passed the technical

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interview screen, but there was still a

lot that I needed to learn on the job.

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So my teammates, my senior

members on the team.

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basically taught me a lot during

my first job as a data engineer.

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Uh, secondly, like one of the advice

that I got from my mentor early on

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is, um, I couldn't figure out, I, I

would always meet people and they were,

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they were always like so passionate

about specific topics, specific area.

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And I wasn't really like

passionate, passionate about it.

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I think I was doing data

engineering at that time.

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So I asked my mentor,

like, what should I do?

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I know I'm not like really

passionate about something.

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In particular, like I like data

engineering, but I don't know

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if I want to do that long term.

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So his advice to me was sometimes

you find what you're passionate

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about and sometimes you don't.

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And if you don't know what you're

passionate about, you still keep going

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and eventually you'll figure it out.

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So that's exactly what I ended up doing.

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I did data engineering and I

found a data scientist role.

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And that, for me, like, this is, I

knew, like, that's the exact next

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thing that I want to do and I pivoted.

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Having the right mentors by my side,

having the aptitude to like pivot and

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learn new things has been like really,

really, really helpful in my career.

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And lastly, I, I, I would, I want to

say like luck definitely plays a role.

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You being at the right place, right

time definitely puts has some,

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there is like some luck involved.

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Like it would be unfair if anybody comes

to you and say like, it's all hard work.

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It's not all hard work.

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It's hard work you putting in the work,

but also like you have to be at the,

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sometimes you have to be at the right

place, right time for things to happen.

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I like to say,

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Avery: yeah, I like to say the,

the harder you work, the luckier

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you get a lot of the time.

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Like, um, if we go back to, you

know, landing your first day at a

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job, you're just a business student.

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You've taken a few like it classes

in, in your college career.

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But at the end of the day,

you're like a business major.

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Like you said, with two kids,

how the heck are you going

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to start interning at Amazon?

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Um, and you went to that networking

event and I think that's kudos to you

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because a lot of people wouldn't have

gone to that networking event because

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one, it's like just another thing to do.

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Two, those networking events, a lot

of the times they're very awkward

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and you have to like go up and like

present yourself to people and you're

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like, hi, I'm Sundance and like, you

should hire me and stuff like that.

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And so yes, like luck had a big part.

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Like they had to be interested

in you at that networking event.

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Um, but just like the fact that

like you showed up, uh, I think is.

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That's a lot of people don't.

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And that's, that's the hard thing is

it's uncomfortable to show up sometimes.

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And then the other thing I want to say,

uh, about you, Sundance, that I think

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has really stuck out to me, uh, we've

gotten to meet, uh, in person for a

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couple of days, uh, a year ago, and then

we've also just gotten interact online is

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like, you're a very clear communicator.

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Um, like you're very good at like

knowing what you want to say and making

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it very easy for the person you're

talking with to understand like, okay,

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this is what's on this means this

is like what she's doing and this

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is what I should do because of it.

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I think that's played like a

huge role in your career as well.

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Would you agree?

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Sundas Khalid: Um, I think that

definitely I would agree with that.

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And I have to give credit to Amazon

because, um, Amazon teaches you a way

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to like communicate in writing and

in talking, like they're very direct.

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When I left Amazon and I went to

Google and I was like asking people

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who were previously at Amazon and now

work at Google, I was like, can you

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give me advice, like, uh, tell me what

I need to do differently and their,

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uh, their advice to me was that like.

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Be a little less, um, I don't want

to say indirect, but like soften,

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soften up the language a little bit.

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So like when you say that,

like I'm not surprised at all.

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Like I can be very direct, yeah.

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Not as direct as I would like to be,

but I can be like very direct and crisp

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and clear in terms of like what I want.

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And I think that has helped me

outside of work, like in content

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creation and like being on YouTube

and, uh, teaching people things.

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So it's been helpful.

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Avery: I agree.

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Yeah.

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Your YouTube audience, your,

your Instagram audience, I

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think, uh, would agree as well.

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Now, like you said, you started off

kind of in this data analyst role.

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And then you kind of pivoted to

data engineering and then you kind

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of pivoted to data scientists.

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And so you've actually worked in

like the big three data professions

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at both Amazon and Google.

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So I'm actually curious, uh, which of

these positions did you enjoy the most?

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Sundas Khalid: Um, okay.

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So I wanted to say You

know, it's a tough question.

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I left data engineering, so

like there has to be a reason.

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I would say like, they're all my

favorite for different reasons.

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I don't want to pick.

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So I would say like data engineering

is my favorite for building.

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Like you get to build things.

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And this is like one of the things that

I miss about being a data engineer.

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Like I don't build things.

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I don't build like data pipelines

or platforms that other people use.

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And I can, at the end of the

year, I can be like, Oh my God.

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These are the number of people that use

my product or the pipeline that I use.

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I think like data analyst

has some aspect of it.

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But like, I definitely miss that from

the data engineering point of view.

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What I don't miss is the on call.

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So that's definitely another topic.

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Uh, the data scientist world is amazing.

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It's just so, so huge in the ambiguity.

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I kind of like to have love

hate kind of like a relationship

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with like the ambiguity.

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But I really love that.

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I can actually take an ambiguous

problem and solve it in data science.

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Uh, when I was working at Amazon

as a data scientist, one of my,

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the ideas that I focused on was

A B testing and experimentation.

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And the coolest thing about A B

testing and experimentation is that

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it would be, like you would run, one

of, some of the tests that we would

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run would be very small difference.

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For example, you would change

the font color from red to blue.

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And you will see like a huge shift in

customer behavior, uh, the purchases,

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the orders, and so like things like

that, that I had previously not

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thought about, like data science

role made me like think about that.

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So I really like that aspect

of it quite a bit, quite a bit.

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In terms of the data scientist

job family, it's humongous.

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Like you can be more on the machine

learning side, more on like the

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product data scientist side, I

would say like my favorite one is

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definitely product data scientist side,

because you get to mix both product.

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So you kind of like a data scientist

times a product manager in one role.

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So you're able to like, think of

more creative ideas and solutions.

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As a product manager, but then

solve them, um, as a data scientist.

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So I guess like I did pick my favorite.

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Avery: There you go.

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It's data scientists.

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You just had to talk it out, I guess.

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Yeah.

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Um, that's very cool.

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I like that.

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You talked about like, okay, yeah.

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Data engineering is building data.

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Scientist is like more experimenting

and trying to figure out how we solve.

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Real world problems with math.

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And then data analyst is somewhere,

um, in, in between now, obviously in

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those different roles, you've probably

been using different tech stacks, but

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there's definitely some overlap as well.

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I'm going to make you choose one again.

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If you had to choose one tool you've used

the most in your career, what tool is it?

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Sundas Khalid: Okay.

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I would have to pick a coding

language and it's going to be SQL.

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And I don't think it's a surprise

to anybody listening to this

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SQL is regardless if you're a

data engineer, you're a data

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scientist or you're a data analyst.

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You have to learn SQL and you have to.

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Not even know it, the basics.

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You actually have to know that vast level

if you really want to grow in these roles.

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In terms of the tools, I would say like

each role uses different set of tools

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and they don't have anything in common.

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So like, I'll stick with

the coding language.

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Avery: I like it.

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I think, yeah, maybe that's not a

surprise that, uh, SQL, it's like

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the most in demand data skill in,

and honestly, all three job families.

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It seems like, you know, I think

Python gets close for, for data

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scientists, but It's, it's really SQL.

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Okay.

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So SQL is the tool you've used the most.

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Do you, do you, do you have a tool that

you like to use more than, than SQL?

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Sundas Khalid: You mean like a

coding language or just like coding

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Avery: language or like Tableau or

Looker, or I don't know, like, is

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there like some tool you really enjoy?

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Sundas Khalid: I think the tool that I

really, really enjoy is Google Collabs,

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um, notebooks, uh, because they are

like so, uh, dynamic, like you can like

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code in R, it's like similar to like

Jupyter Notebook, but I guess like I

260

never really, really got the hang of

Jupyter Notebooks, I've always been

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like a Google Collab person, so I really

love using Google Collab as like part

262

of my job, and what I love about it is

like you can write any language, like

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you can have one notebook and write so

many different languages, to produce

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the results and you can share that code

with just literally a link with somebody

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else that who's going to like take over

your work or like scale it and apply it.

266

Avery: That's huge in, in the workplace,

because like, like you said, like

267

sometimes maybe you're the data scientist

and you're writing the code, but you're

268

not necessarily the person who's going to

put it to scale, or maybe you just need to

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share it with your manager or some other

product owner or something like that.

270

Uh, but it's also big for

those of you who are listening.

271

Who haven't landed a data job yet, because

if you ever do any projects in Python,

272

if you do it like in Jupyter notebook,

you're not going to be able to share it

273

very easily and like doing it in Google

collab allows you to like have a link

274

that you can send to a recruiter or

hiring manager and it just makes like

275

your life easier in terms of sharing

the work that you've actually done.

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You've been at Google for five years now.

277

Um, and, uh, for those of you that

have listened to send us on her

278

YouTube channel, um, you've, you've

maybe heard some of her stories.

279

Um, I highly suggest checking it out.

280

We'll have a link in the

show notes down below.

281

One of the cool things that I think

that you've done, and we'll get

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into negotiation here in a bit.

283

Um, but you, you know, you were

at Amazon, you actually used.

284

Like multiple teams at Amazon, not really

on purpose, but to kind of compete for

285

you that allowed you to kind of get

a little bit more advantageous roles.

286

And then you interviewed in

the past at like Microsoft

287

and got offers from Microsoft.

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And that allowed you to, you

know, get some, some better

289

opportunities at places like Google.

290

Um, but you've been at

Google for five years now.

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Um, can you just tell us like what

your role is and what do you feel like?

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Um, like What you do on a day to day basis

and what you feel like you've learned.

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Sundas Khalid: First of all, like I'm

surprised that you watched all those

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videos because like some of those,

some of that information I know lives,

295

like the Microsoft offer lives in our

videos somewhere deep, so I'm grateful

296

that you watched that, uh, definitely

another story, like how I use my

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Microsoft offer to like get more from

my employer, Amazon at that time, but

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in like my current role, um, at Google

is primarily focused on Google search.

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Uh, so like when you search

on Google, like you'll see.

300

Some ads.

301

So like I work in Google search

ads and then there's another tab

302

that you will see like shopping.

303

So like the ads that you

see in search and shopping.

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So that's the part of my, uh, that's part

of my team and that's what I support.

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So my work is primarily like

focused on like doing advanced

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analytics, like experimentation.

307

Uh, deep insights and kind of like

figuring out what works and what doesn't.

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Um, so it's like a, I would say like,

it's a, it's a hybrid of data scientists,

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product data scientists, and advanced

data analytics all merged into one.

310

My typical day to day depends on

the project that I'm working on.

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So for example, uh, right now that

the project that I'm working on that I

312

told you, like before this call, like.

313

It's a large scale project, and

we've been working on it for many,

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many years, and it's currently

in the implementation stage.

315

And while we're implementing, things

that could go wrong are going wrong.

316

So, my current project is figuring

out, uh, there is a small traffic

317

that we launched, and I'm doing

an investigation to understand,

318

like, what exactly is happening.

319

So, like, doing deep dives there

to, like, root cause the problem.

320

That's my current focus.

321

Last month, if you ask me what my

day looked like, my last month,

322

my day was, um, my days was

focused on my, on experimenting.

323

So we were running a lot

of like sequential testing.

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So I was doing a lot of like experiment

analysis, trying to understand how

325

different arms of the experiments

have performed and what decisions

326

we need to take and whatnot.

327

Avery: Very cool.

328

That's, that sounds very cool.

329

It's so, it's, it's so

neat to like hear that.

330

I like it.

331

Oh yeah, there is data scientists

working on this product that I literally

332

use every single day, you know, and

they're improving the product based

333

off of what I do with the product.

334

So I think, uh, that's,

that's really cool.

335

And like for the, for the years that

you've been there, like, what do you

336

feel like you've taken away as like

your number one, like piece of advice?

337

Like, for instance, if

you were to go back.

338

To Sundance five years ago on day one

of starting Google, you actually have a

339

video, I think, where you did like the

day one of Google or something like that.

340

Uh, if you were to go back and

talk to that Sundance, what

341

advice would you give her?

342

And what would you tell her that,

that maybe you, you wouldn't

343

have realized or thought back?

344

Sundas Khalid: So let's go back a bit

in terms of like, when I was at Amazon.

345

So Amazon was my first job and

I spent about six, seven years.

346

If you like count my internship

time as well, my internship was

347

eight months long, which is like

not a typical internship time.

348

time.

349

So I always wanted to experience industry

outside because Amazon is all I knew.

350

So when I started looking for jobs, like

I had a few companies in mind that I was

351

interested in, and Google was one of them.

352

And let me just say that if I hadn't

joined Google, or if I hadn't left Amazon,

353

I wouldn't know like what it's like, you

know, Experiencing different work cultures

354

and figuring out what I actually like.

355

I think one of the biggest learning for

me personally is learning about like what

356

type of culture, work culture and work

environment I want to be part of, uh,

357

what I need to look for in my next job.

358

So one of the big things

that I immediately learned at

359

Google or like noticed is the

culture and how nice people.

360

Uh, for example, like I, my Nugler

orientation was in New York.

361

Um, and I was meeting some of my teammates

there that I've never met before.

362

And they were like, where are you based?

363

I'm like, I'm, I'm in Seattle.

364

And their response was like, love that.

365

Love that.

366

I'm like in my head, I'm like,

why are they saying love that?

367

It's, uh, I've never even met them.

368

And this is the first

time I'm meeting them.

369

Maybe just, they're just

trying to say that to me.

370

And then.

371

Weeks past, months past, like this

was like a normal people behavior.

372

And eventually it kind of like

rubbed onto me as well, where

373

I picked up that language.

374

Um, so I would say like the

biggest learning for me has been

375

like just seeing how people first

culture actually looks like.

376

And I'll talk, I'll definitely talk

about like how Google has been an

377

inspiration or has like helped me

learn, become financially literate.

378

Because if I hadn't joined

Google, I don't think I would.

379

I don't want to say ever, but like, I

don't think the chances of me becoming

380

a financially literate person would

have happened if I hadn't joined Google.

381

So the number one thing definitely

stands out is like the culture and

382

people like, uh, Google has some of

the nicest people that I've ever met.

383

And what I like to tell my

friends is like a different world

384

inside that everybody's just.

385

Um, really nice to talk to.

386

It's

387

Avery: it's

388

Sundas Khalid: pleasant.

389

It's always pleasant.

390

Just so, I

391

Avery: mean, I think they give

those vibes off like, uh, like the

392

campus seems fun and like playful.

393

I've seen some of like

videos and pictures there.

394

And, uh, I mean, like even like

the logo feels a little bit, maybe.

395

More playful than other companies.

396

And it is, I think what you said is really

important that like, you need to go out

397

there and try different companies, um,

and maybe even different industries.

398

Because, uh, what I found in my

career is I started my, my data

399

career at a really small biotech

startup that had like 15 employees.

400

I love them.

401

Shout out to vapor sense, but

like, you should have seen my desk.

402

Like it was, it was kind of like a

box basically, like in a closet and

403

uh, like I didn't have nice equipment.

404

And so when I got an offer to go to

Exxon mobile, uh, at this huge campus

405

down in Texas, like this awesome sit

stand desk, I was like, Hey, I need

406

to try that and see what it was like.

407

And then I got there and I was like.

408

Crap.

409

I hate working for a 70, 000 or not

70, 000, 70, 000 person company,

410

uh, in manufacturing and I would

never, I would have never known that.

411

And I'm glad I still did it because I

would have always been like, well, what

412

if I like working for a big company that

gives me nice perks, but I actually,

413

like when I was there, I realized, crap,

I want to go back to like the rag tag

414

team, you know, of like a small company.

415

And then I started my own company.

416

Now I'm a company of one and I like that.

417

Right.

418

So, um, I think it's

really cool that like.

419

At the end of the day, like we're

all, we're at work for, you know,

420

40 hours a week, most of us, right?

421

Something like that.

422

Maybe more, maybe less.

423

Like we want to be doing something we

actually enjoy with people we enjoy

424

in an environment that we enjoy.

425

And obviously the money is important,

but like if, if you paid me a bajillion

426

dollars, okay, maybe not a bajillion,

but if you paid me a lot of money

427

to do something I didn't enjoy.

428

A million!

429

Okay, if you paid me a million

dollars, but I hate my life,

430

I don't know if I would do it.

431

If you paid me a billion, I'm probably

in, but a billion, I don't know.

432

Sundas Khalid: Listen, you

get that million, you work for

433

a year, and then you retire.

434

So.

435

Avery: Perfect.

436

There you go.

437

So obviously one thing that

people are really interested

438

in is like this new wave of AI.

439

Do you have any tips on like for people

of how they could be using AI at work?

440

Sundas Khalid: Yeah, um, you know what?

441

That's a great question because AI is

like the new hot topic and literally

442

anyone, everyone is talking about it.

443

So if somebody in this world who doesn't

know what ChatGPT, Gemini or any of

444

the generative AI tools are, I don't

know like who you are, please identify

445

yourself because Literally, everybody

knows it and have at least tried once.

446

Um, in terms of like using it at

work, I think it's becoming, uh, more

447

and more popular in the workspace.

448

Uh, so some of the things that

I have personally done and

449

use AI for is like coding.

450

So let's say if I'm writing a SQL code

or a Python code, and I can either,

451

there's like, um, There's an AI built in

that can help me like finish the code.

452

I think GitHub AI, what is

GitHub's version called?

453

Avery: Copilot is it?

454

Copilot,

455

Sundas Khalid: yeah, literally basically

Copilot and all of these other tools

456

that like helps you finish coding.

457

So like coding is definitely

one of the use cases.

458

So if you are a coder, definitely

take a look at, look into that.

459

One of the things that I'm really,

really proud of is, like, I wrote

460

a document in less than 30 minutes.

461

It's a two page document using Gemini,

which turned out to be really good.

462

I did not use the exact copy of

the Gemini, just for the reference.

463

Um, I basically got an outline, got

some, some sections to fill, and then

464

I turned it into my own language.

465

Sometimes when you stare at a black

piece of paper, it's just difficult

466

to start, so having Gemini built

in, I'm able to kind of like, have

467

it start, and then I like, I, I

basically jump in and like, take over.

468

Then email writing and email summarizing,

like sometimes when you have like, long

469

You can literally use email that is built

into like Gmail and other email tools to

470

like summarize the large thread and help

you understand what exactly it is saying.

471

So it's like a great time saver.

472

The two, the last two that I want to

mention is like summarizing Google Slides.

473

Sometimes I get access to like

these large decks that I really

474

do not want to go through.

475

So I will just ask Gemini to

like summarize these for me.

476

And then my last one, my favorite

one so far has been Notebook LM.

477

Um, I don't know if you have

tried Notebook LM, but it's

478

literally, it's just, Just mind

blowing what it's capable of.

479

You can basically actually did a YouTube

video on this where I did a walkthrough.

480

I'm writing my next newsletter is going

to be about notebook LM as well, but

481

basically you plug in your documents.

482

You can even link

articles, YouTube videos.

483

Um, and you can ask it to like,

uh, create summaries, uh, for you.

484

It's basically like your own tiny

rag system that you have built using

485

NotebookLM that you can like ask

questions that are like specific to

486

the documents that you have imported.

487

It can also create a podcast for you.

488

I mean, I can talk about

it for a very long time.

489

I love NotebookLM, like one of the

projects that I mentioned earlier,

490

I'm actually using NotebookLM to like

scale all the work to global teams.

491

Because notebook LM can literally, I

can import like the dozens of documents

492

that I have from last two years, um,

and like build it one repository.

493

And instead of like somebody who is like

onboarding on this project, instead of

494

like reading through every document,

they can just like ask questions to

495

notebook LM and like get an answer,

which I think is really, really cool.

496

Okay, I'll tell you one thing.

497

I don't need to use a tool to figure

out if you wrote something with chat

498

GPT or Gemini, like I can, I can read

your script for like 10 seconds, and

499

I'll know like you wrote something.

500

So recently, we're going off topic, but

recently, like, I was interviewing for

501

my personal assistant position and there

were like 500 applicants and after reading

502

those 500 applications, like, I kind of

figured who wrote with ChatGPT, who wrote

503

with Gemini and like, what are they doing?

504

So, use it at your own risk.

505

But it's a great starting point, but

it's not, it shouldn't be your end point.

506

So I won't be watching videos

that are just had deputy

507

scripts because I can tell,

508

Avery: I like what you said earlier.

509

It's like a warm start.

510

You're not starting from

a blank, blank slate.

511

Um, I know I've been hiring a lot recently

and there's been multiple candidates,

512

I would say like close to 10 to 20%.

513

That forgets to like put my name,

like it just has like the blank, like

514

brackets that chat GPT gives you.

515

And I'm like, guys, come on.

516

I can't trust you.

517

This is The funny thing

518

Sundas Khalid: is like all of them

were using the same structure, like

519

how in the world you all came together

and just use the same structure.

520

Like this section is going to have

this, this is going to be this section.

521

It was just crazy.

522

Like, please, if you're like job

searching, please don't use like raw chat

523

GPT output, like you're just risking.

524

So your, your application by doing that.

525

Avery: I love it.

526

Okay.

527

Thanks for your AI tips.

528

I appreciate it.

529

Uh, let's talk some more about financial

literacy, because you said if you'd

530

never been at Google, you may have

never gotten to financial literacy.

531

You cover, you cover a lot in your

content, um, which is important, right?

532

Because.

533

As much as you and I love data and

everyone else, we probably wouldn't

534

be doing what we're doing right now

if it wasn't for the fact that like,

535

we want to be like financially secure.

536

Um, and I love how

transparent you've been.

537

You've done like a whole like 10

year salary, um, like documentation

538

of like where you started.

539

It was like something like 40, 000 to like

over 500, 000 in the last like 10 years.

540

So what made you like, what was

like the thing that made you

541

get into financial literacy?

542

Sundas Khalid: Yeah, no,

that's a great question.

543

Um, I think it all started when I

attended this one talk at Google

544

and it's actually on their YouTube.

545

Um, this was by an author called,

uh, his name is JL Collins.

546

He wrote The Simple Path to Wealth.

547

The book is really popular now.

548

Uh, but basically he came to one

of the Google talks and I ended up

549

attending, which I wasn't planning to.

550

And the way he talks is like, he talks

like he is like your uncle and he's like

551

trying to explain you like, what are.

552

What is investment?

553

What you should be investing in?

554

What is a retirement account and whatnot?

555

Ended up buying his book,

ended up reading it.

556

And that's where like my, like that,

me attending that like 30 minute

557

talk had Google basically inspired

me to get into financial literacy.

558

After that, like ended up reading Ramit

Sethi's book, I will teach you to be rich.

559

Like these two books combined literally

gave me everything that I needed to know.

560

And the funny part is up until

this point, like I was in the

561

industry for about six years.

562

At Amazon, I had no idea that

Amazon offers 401k match.

563

I never really invested in 401k.

564

I left that 401k match on the table.

565

And I had all the money

in my savings account.

566

Like all I knew was savings.

567

So I just kept saving.

568

So every time I went to my bank

account, like the bank tellers,

569

the managers would come out and

they would be like so nice to me.

570

They were like, why

don't you come sit here?

571

I was always wondering like,

why are they so nice to me?

572

And after I became financial

literate, I realized like they were

573

nice to me because nobody keeps.

574

That much money in their bank

account, like people invest anyways.

575

So that led me to like openly talking

about financial literacy because

576

there are many people like me who

don't fully understand like how to

577

actually make your money work for you.

578

Like, I don't have any like certifications

or like, um, what is the accolades to say?

579

Like I'm a financial educator.

580

Like I'm just sharing what I am doing.

581

And that's what I started doing.

582

Like I started sharing like what

I'm doing, like, this is what

583

I'm reading right now, this is

what I'm investing in right now.

584

And it turns out like I have inspired a

lot of people to like, become financially

585

literate, like two books that I

mentioned, like I've shared with thousands

586

of people, they have read it too.

587

And eventually, uh, I was like, okay,

how can I like make more impact?

588

Because I'm so passionate

about this topic.

589

And that's when in like 2021, I

decided that, okay, I'm going to like

590

volunteer my time to help other people

negotiate their salaries because.

591

Another story, which I cover in detail

in my course, but basically when

592

I got my data engineer offer from

Amazon, it was way, way, way below.

593

Just to give you an idea, my first

year salary was 65, 000, which is

594

for a data engineer role based in

Seattle, which is high cost of living.

595

Anyways, that led me to being on a path

to figuring out what my market rate is.

596

Eventually when I learned all those things

for myself, I wanted to help other people.

597

So then in 2021, I started

volunteering my time.

598

If somebody had an offer, like

I'll go and basically help them

599

like negotiate their offer and

give them strategies and whatnot.

600

Eventually I realized like that is

not scalable with a full time job.

601

I cannot just get on a call with

everybody, uh, to kind of like

602

give them consulting and whatnot.

603

I'm, I don't know if you've ever

done like one on ones, but like

604

those are difficult to scale.

605

Avery: I did 250 last year.

606

Sundas Khalid: I'm on the death.

607

How do you do that?

608

Avery: Uh, I did, I

tried, yeah, it's hard.

609

It's really hard.

610

Yeah, I totally get it.

611

Sundas Khalid: Yeah.

612

It's hard.

613

And you hit a limit at some point.

614

You were like, okay, there's

no way I can do more.

615

So then I was like, okay, I, how

can I like continue scaling this?

616

So that's when I ended up building the

course that I have right now, which

617

is on salary negotiation, where I

like share all the tips and tricks on

618

how somebody, anybody can learn, uh,

salary negotiation strategies and skill

619

and can negotiate their own salary.

620

The course that I have is like

specifically focused on tech because

621

that's what my specialization

is like, I guess my area is, but

622

yeah, happy to talk more about it.

623

I actually have a special discount,

a coupon code for your audience.

624

So, um, yeah, and I'll share it with you.

625

You can, it's a, it's Avery20.

626

So like if you go to the website, which

you can link here and use the coupon

627

code Avery20 to get 20 percent off.

628

Avery: Okay.

629

Awesome.

630

Yeah.

631

I, you're being humble because, um, like

obviously like, like, uh, you, you've been

632

really good at, great at this, but like

in one year you helped 50 different women.

633

Negotiate like 1.

634

4 million of extra incremental salary,

not like total salary, incremental salary.

635

Um, and I did the math.

636

I'm pretty sure.

637

I think that's like 30,

000 per person on average.

638

And I just want to like highlight

this to, to everyone listening that

639

like some of this is offering this,

obviously it's, it's paid, but like.

640

And you might not get 30, 000 out of it,

but you're going to get a lot out of it.

641

And the coolest part about salary

negotiation, in my opinion, and

642

Sundance, you're the expert here.

643

So correct me if I'm wrong.

644

The majority of the time, the worst thing

that happens is they say, no, sorry.

645

Right.

646

And the best thing that

happens is they say yes.

647

And the most likely thing is they

meet you somewhere in the middle.

648

And so like, in my opinion, correct me

if I'm wrong, like there's not really

649

a downside for asking for more money.

650

The majority of the time.

651

Sundas Khalid: Yeah, like unless until

the recruiter says this is the last and

652

final offer, like you, you wait for those

words and unless until the recruiter says

653

the last final offer, it is not a final

offer, basically when they give you the

654

first offer there is still room, they

leave room for negotiation because a lot

655

of people do negotiate even though like

there was a study done like 50 percent

656

of the people Don't negotiate, which is

surprising, but when the recruiters are

657

giving you that number, they are leaving

room for negotiation for you to ask more.

658

And when you accept that and

believe me, like I've been there.

659

Uh, when you go through that

rigorous job market, like that we

660

are currently in, and then you go

through like so many interviews

661

and then you finally get an offer.

662

You're like, thank God

I'm so done with this.

663

I'm like, so over it.

664

Like the first offer or like

whatever offer number you are on.

665

You get it and you're like,

I want to just sign it, lock

666

it, and like be over with it.

667

Just like hold on a little more and

just stay patient in that stage.

668

Because chances are it could be just

you simply asking the recruiter and they

669

might come back and say like, yes, I can

increase your compensation by this much.

670

Don't accept without asking,

um, and listen for those

671

words, a last and final offer.

672

Cause, but even with that, like there's

a lot of strategies that you can use,

673

for example, like competing offer, uh,

the market research tools and whatnot.

674

So there are ways to negotiate, uh,

but don't accept your first offer.

675

Avery: I just think this is so cool that

you're doing this because, um, I honestly

676

think it's one of the best investments

anyone can make because when you've gotten

677

to that point where they're literally

saying, okay, we're going to offer you.

678

Like they don't want, they're not,

they're not looking to get rid of you.

679

You're looking to hire you.

680

And so if you ask for more money,

it's not going to be, they're

681

not going to be like, Oh crap.

682

Like, nope.

683

See you later.

684

You're not getting this job offer.

685

Like, as long as you're like

really appropriate and you, you

686

do do it professionally, you're

probably going to get something.

687

You might get nothing,

but at least you can ask.

688

Um, and the other thing I want to

just really highlight, you know, going

689

back to the financial literacy thing.

690

Is, you know, let's say, let's say you

negotiate and let's just say you get,

691

let's just make it somewhat smaller.

692

Let's make it 3, 000 instead of 30, 000.

693

You have to realize that that 3, 000

is going to be there every year, the

694

rest of your life for that salary.

695

Um, so it's basically compounding.

696

So like, let's say you negotiate

3, 000, that's an extra 3, 000.

697

Like you might not get that raise for

a year, for two years, for three years,

698

you might not get a 3, 000 raise.

699

And so you're getting that up front

and that's just going to compound

700

upon every single year, the rest

of your life that you're working.

701

So it's, it's almost like you're not doing

3, 000 and I'm really bad at compound

702

interest and, and stuff like that.

703

But like, yeah, 3, 000 is actually

like, you know, 20 years down the

704

line worth like something like 50,

000 or something like much, much more.

705

Sundas Khalid: Right.

706

And the, the, the part about like, ask

if you're able to get that 3, 000, for

707

example, let's say your compensation

for software was 100K and you end

708

up negotiating and now it's 103K.

709

So let's say next year when it's

performance review, like you are given

710

the annual raised and most big, major mid

sized companies, you're giving even like

711

the smaller companies, like the, your

annual raise is based on your base salary.

712

So.

713

You're going to be given, given up

certain percentage, let's say 10

714

percent raise on that 103 number

instead of the a hundred number.

715

So like it does add up eventually.

716

Avery: Yeah.

717

Which I think is incredible.

718

So, um, that's super cool.

719

You're, you're, you're

one of the best at it.

720

You know, you've, like you said in,

in this video, we'll have a link to

721

it in the description down below.

722

You've gone from like 40, 65,

000 to, you know, over 250, 000

723

to a lot more money than that.

724

Just in negotiation, you've done

different tactics of like, Oh,

725

you've gotten competing offers from

Microsoft and, you know, Amazon

726

and all these different things.

727

Um, so I'm really excited about

this and I think, uh, people

728

can really learn from it.

729

We'll have a link in the show notes down

below and you can use that coupon code.

730

Send us, thank you for

giving us to the audience.

731

That is super exciting.

732

Avery 20.

733

Um, and where else can

people, people find you.

734

Sundas Khalid: Oh, my God.

735

I'm everywhere.

736

Um, I was, I'm actually speaking

at another, another live webinar

737

later today, and I'm like, trying to

figure out which social should I get?

738

So I'm literally everywhere.

739

I'm on YouTube, Instagram,

TikTok, LinkedIn.

740

I just started a newsletter

this year, uh, on Substack.

741

So it's my full name.

742

You can use Sundas

Khalid on Sundas Khalid.

743

Um, LinkedIn on YouTube and then on

Instagram and TikTok, you can find me.

744

It's Sundas Khalid, but there's

an extra D, so like two Ds.

745

Uh, and you can link them below

and then my website, SundasKhalid.

746

com.

747

So if I ever, my accounts, my

social media accounts ever shut

748

down, I will still have my website.

749

Yeah, I was going to say like,

definitely subscribe to my newsletter

750

because that's something that is new

to me and I'm planning to put a lot

751

of work into newsletter this year.

752

So, uh, if you want to hear from me, like

in your inbox, like that's the way to go.

753

Avery: Perfect.

754

I look forward to that.

755

Uh, I, I really enjoy, uh, all of a sudden

this is social medias, but specifically

756

I think her YouTube videos and her

Instagram videos are really great.

757

Well, perfect.

758

We'll have all those links

in the show notes down below.

759

Sundas, thank you for coming on.

760

Sundas Khalid: No, thank you

so much for having me, Avery.

761

And I love that we have that

blue and red vibe going on.

762

It was perfect.

763

It worked out.

764

So

765

Avery: fun.

766

Sundas Khalid: Awesome.

767

Thank you, everybody.

768

Bye.