203: There’s No More Data Analyst Jobs

Speaker: 00:00:00

Avery Smith-1: There's no

more data analyst jobs left.

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: 00:00:02

That's what I keep hearing, especially

on YouTube, but that is a complete lie.

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In today's episode, I'm gonna show

you why I think there's actually

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: 00:00:09

a lot of data analyst jobs left

and why you should not panic.

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: 00:00:13

But if you're new here,

my name is Avery Smith.

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I'm a senior data analyst, and I

make content about how to thrive

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in your data career, especially

if you're just getting started.

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The real question is who is

saying that data jobs are dead?

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Who's saying that there's no

more data analyst jobs left.

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And really I think it comes

down to, there's three different

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groups that are sharing this

narrative all over the internet.

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The first group is YouTubers who are like

me, and they are carrying this narrative

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around that data analyst jobs are dead.

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There's a great data analyst crash

that has occurred or is coming,

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that there's no more data jobs.

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And I'll be honest, I've even been

complicit in some of my titles and

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thumbnail choices here on YouTube.

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So why are YouTubers creating these titles

and these contents, why are they spreading

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this message around if it is a lie?

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Well, honestly, it's because

you guys click on those videos.

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I shared this in a recent

episode, but I actually AB

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tested two different thumbnails.

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One that was positive, like there's

lots of data jobs in the future,

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and one that's negative, that

there's no data jobs in the future.

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The video content stayed the exact same.

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The thumbnail stayed the

same, and the negativity won.

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Everyone wanted to

click on the negativity.

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It actually won by two times.

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So basically two times more

of you guys clicked on that

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video than the positive one.

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So it just really goes to show, especially

on YouTube, that negativity wins.

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But we've already known that because

that's why the news is negative.

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Like we as humans, for some reason,

just love negativity and for YouTubers,

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Hey, if we can create videos that

you guys love, then we wanna do it.

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But personally, I want to be honest,

I'd rather be honest than be negative.

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I'm an optimistic person, so I try to make

my episodes as optimistic as possible.

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Of course, with keeping it realistic,

I don't wanna just gaslight you guys

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and tell you that there's lots of

data jobs left if there are none.

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But I wanna keep it honest and optimistic.

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Now, sometimes I might use a title or

a thumbnail that might be more negative

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so I can get more people to click.

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But I justify that because my message

is honest and uplifting and optimistic,

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and in order for more people to get

that message of, Hey, there is lots of

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data jobs, you can actually do this.

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We might need to lure them in

with some sort of negativity.

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The second group who is saying there's

no more data jobs left are job seekers.

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And this actually makes sense because

if you're trying to land a data job

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right now, it can feel like there's no

data jobs left because you're applying.

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To hundreds of data jobs probably,

and not getting any calls back,

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not getting any interviews, and

that can be really frustrating.

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And so you can be like, oh my

gosh, there's no data jobs left.

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I can't land the role, I

can't land an interview.

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This sucks this, you know,

industry, this career isn't for me.

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But it's important to highlight that

these job seekers, although their

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experiences are lived and true.

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It's not really data driven, it's

not really analytical, it's just

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more of an experience they've lived.

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There's no actual data or truth behind it.

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But look, I get it.

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There's ghost jobs out there.

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There's fake jobs out there.

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There's scam jobs out there, and

landing a real job feels impossible.

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So I totally get if your job secret

and you feel like there's no data jobs

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left, because that's how it feels.

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It makes sense.

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The third group that is

sharing this message across

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the internet are AI maximalist.

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And these are people who really believe

in ai, that it's the future, that there's

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going to be a GI, that robots and, uh,

AI agents are gonna rule the world.

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And of course they think if they

think that they're gonna think there's

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no more data jobs, nevertheless,

no more any jobs that these agents

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will just take all of the jobs.

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So those are the three groups

that I think are really spreading

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this message across the internet.

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And as a bonus fourth group, I would just

say pessimists in in general, people who

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who see the cup as half empty instead

of half full will think that there's

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no jobs, that everything's doom and

gloom, that everything's going to end.

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If you're one of these pessimists or

people who think there is no more data

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jobs, or that data jobs won't exist in

the future, I hope that I will be able to

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change your opinion during this episode.

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What is the evidence?

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Well, I'm gonna show you six real

pieces of evidence that data jobs aren't

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dead and they even might be thriving.

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The first piece of evidence I want to

show you comes from a research study

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done by Bloomberg where they basically

analyzed 180 million global job postings

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from January, 2023 to October, 2025.

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This was all scraped from RA and

they found some really interesting

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things I wanna share with you.

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One of their key takeaways

was that data related jobs are

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holding up despite AI tools.

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So basically despite what you might

be thinking AI tools can do to replace

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a data analyst, data scientist, we

don't see that in industry yet, and

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those roles are actually growing.

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It basically says that even though

AI tools can write SQL queries or

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write Python code, that the data

analyst or the person actually using

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those tools is still very valuable.

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Despite these AI tools, knowing what

questions to ask still really important.

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Knowing if you can trust data

or if you could, what data's

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clean and what data's not clean.

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Still really important.

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Knowing how the data and the analysis

that you find ties into the business and

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being able to convince stakeholders and

non-technical people of your findings

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still really important and really needs

a human to do all of those things.

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One of the things it also mentions

is you can kind of use software

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engineering and software development

jobs as a proxy for data jobs.

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'cause they're very closely related.

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They're both very technically focused.

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They're a little bit different.

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But you can kind of see some

similarities in software development

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and data analytics and data scientists

and all those different things.

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And that's really key because one of

the things that actually found in this

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study was that software engineering

jobs have stayed really resilient.

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Of course, we've seen some

decrease in front air engineering

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and mobile engineering as

that's gotten easier and easier.

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But other things like machine learning,

engineering, data engineer, backend

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engineer, data scientists, and

honestly, these aren't really even

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software engineering jobs almost.

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These are data jobs.

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So like software engineering is

doing well if it's data related.

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And all the things that we're talking

about on this channel is all data related.

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So basically with ai.

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AI is just so dependent on data

and we are the best people fit for

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talking about data, thinking about

data processing data, analyzing data,

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structuring data, shipping data.

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That's us.

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And the best place to start for any data

role is a data analyst, because it's

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one of the lowest on the totem pool.

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It can get, obviously very senior as

you go on, but it's like a really good

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entry point where you could become a

data scientist later down the road.

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You could become a DevOps

engineer down the road.

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You could become, you know, a

data engineer down the road.

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This is like the entry point of

the data world, and this data

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family, this data role kingdom

that we play in is the number one.

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Kingdom, the number one job family

for handling ai, maybe other than

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software developers, but you could

argue that we know a little bit

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more about data than they do.

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The second piece of evidence I want

to present to you is from live data

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Technologies, and they use a special

proprietary software to basically

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figure out how many different data

analysts are there in the world.

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How many different lawyers are there in

the world, how many different, you know,

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real estate agents are there in the world.

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And we can actually see that

data analytics, data analyst

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jobs have grown since 2021.

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Uh, about 12%.

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Now, has it been stagnant

in the last two years?

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Uh, maybe.

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But you have to remember that

in: 2021

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There was a lot of over hiring

going on, so the fact that it really

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hasn't gone down is a good sign.

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I think this year we'll start

to see this grow a little bit

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more like data engineering.

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I think data engineering has really

exploded because once again, in

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order for AI models to be good,

you need good data engineering.

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In order to have good data engineering,

you need to have good data engineers.

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And honestly, I don't really

ever see people just starting

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from zero to data engineer.

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They always start in some different role.

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For instance, like a software

engineer or the second most common

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one I think is a data analyst.

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You go from data analyst, data engineer.

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So if you want to ultimately work

in data engineering, a data analyst

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is a really first good landing place

because it's way easier to become a

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data analyst than as a data engineer.

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There's a lot less tech that you

have to know, a lot less programming,

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and you can start to get paid to

learn data engineering on the job.

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So once again, no evidence here

that data analyst jobs are dead.

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The third piece of evidence I wanna

look at actually comes from the World

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Economic Forum, and they did this

big study to try to figure out what

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they think the top growing jobs are

going to be in the next five years,

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even with all this AI disruption.

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And if you check out this graph that Euro

News made of their data, you'll actually

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see something that's quite promising.

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A good chunk of these top

jobs are very data related.

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Now, of course, you're not gonna see data

analysts necessarily in the top five.

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You think it's number

eight or number nine.

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But big data specialists, like

big data specialists start their

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careers as data analysts, AI and

machine learning specialists.

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Once again, if you want to become

that, that's gonna take like three

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years to learn all that stuff.

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So start small as a data analyst.

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Data warehousing specialists.

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That's basically data analysts.

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Data engineers, data analytics, engineers.

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And what these bars or these numbers

represent is the percent that they're

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gonna grow over the next five years or so.

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So we are seeing a lot of growth in

these jobs over the next five years,

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according to, you know, one of the most

prestigious organizations in the world.

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So I don't think they think

that data analyst jobs are dead.

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My fourth piece of evidence comes

from another really prestigious

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organization, and that's the Bureau of

Labor Statistics from the United States.

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This is one of the biggest organizations

actually tracking employment

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and job statistics over time.

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And what do they think about data jobs.

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Now they don't actually specifically

analyze data analyst jobs as a job

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role or job family, but they do

data scientist jobs and let's see

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how they do over the next 10 years.

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The BLS basically predicts that the data

scientist job will grow 34%, and that's

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actually the fourth fastest growing

job family in their entire report.

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So honestly, if you want a career that

is growing over the next 10 years,

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the BLS thinks that this data science

world that you can play in is one of

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the best places you could possibly be.

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And you can actually look at

this graph and see how that

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compares to what they think all

occupations will grow in on average.

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And that is just 3%.

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So like literally, this is one

of the best places you could.

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And not only is it data scientist

jobs, it's like really all data jobs.

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They said this tied to the increased

use of AI is this massive increase in

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the volume of data generated, which

is expected to fuel job growth among

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many mathematical science occupations.

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Relevant occupations include data

scientists, actuaries, and operations

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research analysts, all of which are

projected to see job growth of at

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least 20% between 2024 and 2034.

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Placing them all in the top 15

fastest growing occupation lists.

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And I actually created a little bit

of a table for you that shows that

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computer and info research scientists,

statisticians, market research analysts,

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and database admins and architects are

all supposed to grow quite a bit more

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than average over the next 10 years.

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Once again, this prestigious organization.

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Not really indicating that

there's no more data jobs.

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If anything, there's gonna

be a lot more data jobs

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now in the world and that is X or Twitter.

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Put your political leanings aside.

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X is still used as one of the places

to get up to date information and

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there's been a huge growth in automatic.

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Coding, basically programming, coding

over the last six months where it's

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like, oh, software jobs are dead.

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You know, Claude code, it's so good,

it's gonna replace, you know, my, my

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software developers and there's gonna

be no more software engineering jobs.

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I'm sure those videos exist,

uh, on YouTube as well.

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And we've seen a really weird twist in

the last few weeks where there's actually

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a lot more software development jobs.

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They're growing.

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So software jobs aren't dead.

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They're growing and if there's one

thing we know about software jobs is

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they kind of mirror these data roles.

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There is a little bit difference

between the two, right?

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Where obviously data people aren't

really creating software and software

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aren't really analyzing data.

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But there is a lot of overlap and a

lot of similarities and I think AI will

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enhance or disrupt them almost equally.

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Maybe not quite, but we can learn a lot

of lessons from software engineering.

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'cause I do think they're about one to

two years ahead of the data industry

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in terms of using and utilizing ai.

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So in the future we might see a

similar trend where maybe there is a

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little bit less data jobs, who knows?

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But then I think it will

bounce back as well.

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And to be honest, that's every

market, for every history of time,

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there's gonna be ebbs and flows

on the number of jobs available.

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No matter if you're a firefighter, no

matter if you're a teacher, no matter

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if you're a nurse, there's gonna

be ups and there's gonna be data.

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My sixth piece of evidence is that this

isn't actually a new question, although

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there's a lot of people saying that

data jobs are dead or questioning if

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data jobs are gonna die right now in

: 2026

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This actually isn't a new question as

almost existed as long as the term data

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analytics and data science has existed.

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Let me actually show you a few examples.

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So in 2021, before chat, GPT even

existed, my good friend Ken G,

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wrote a medium article asking,

is data science dead in 10 years?

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That was really before all of

this, you know, LLMs and generative

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AI had really taken off, and

he was asking that question.

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We're about exactly halfway through

that mark, and of course, we're

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still yet to see, but so far

there's still a lot of data jobs.

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In fact, there hasn't

been really a decrease.

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As I showed you guys earlier, uh,

there's really just been either a

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stagnation or a slight increase in 2017.

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One of the most trusted data

organizations, Gartner, that

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is like consulting and software

evaluations and stuff like that.

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They had a headline that says.

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More than 40% of data science

tasks will be automated by: 2020

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Well, guys, we're six years past 2020.

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I definitely don't think 40% of data

science tasks have been automated.

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Now you can say they were just early

on their prediction, or you can

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say that they're flat out wrong.

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In the 2010s, there was a lot of

hype on no-code tools in general

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and things like DataRobot and

Alteryx and all these different like

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no-code, uh, analytics platforms.

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And those were gonna take

all of the jobs back then.

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Well, it's not really true.

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Those just created more jobs and we still

have lots of data jobs more than ever.

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Actually in 2016, people were

on subreddits asking, is data

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science getting overcrowded?

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People think it's overcrowded

today, people thought it was

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overcrowded 10 years ago.

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If they could see today,

they'd have no idea how.

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Under crowded.

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It was at the time, who knows, in 2036

we might be saying the exact same thing.

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Is data science overcrowded?

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And we didn't know how good, uh,

you know, that we had it in: 2016

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how good it was going to be in 2036.

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In 20 15, 1 of the biggest data blogs

ever, Katy Nuggets actually ran a

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poll that asked, will data science

tasks be automated by: 2020

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And a lot of people thought

it was going to be automated,

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everything was gonna be gone.

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And guess what?

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We've passed that.

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It's not automated.

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There's still lots of jobs, there's

lots of opportunities for us.

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So, you know, even 10 years

ago people were thinking this.

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And as early as in 2013, a really

popular data author wrote a blog

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post titled The Bursting of the Big

Data Bubble Guys, that was in: 2013

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I don't think the big

data bubble has burst yet.

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It's only grown bigger

and bigger and bigger.

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So if in 2013 they thought

they were in a bubble.

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How big is the bubble today?

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How much bigger is data today

than it was in: 2013

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thought it was gonna be over.

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: 00:14:06

But my advice to you at this

point so far is don't panic.

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: 00:14:10

Don't freak out.

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: 00:14:11

Don't give up, because it seems like

there's gonna be no data jobs left.

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: 00:14:14

There's gonna be data

jobs left, I promise.

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: 00:14:16

Personally, I think you should

live by this quote, which actually

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: 00:14:18

came out of a Matt Schumer article

that went really viral on X,

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: 00:14:22

called Something Big is Happening.

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: 00:14:23

It's kind of an AI doomsday type article,

but he said something really important at

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: 00:14:27

the end about a lawyer speaking about his

lawyer friend that has just dabbled in ai.

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: 00:14:31

He said if it stays on this trajectory,

it being ai, he expects it will

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: 00:14:36

be able to do most of what he does

before long, and he's a managing

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: 00:14:40

partner with decades of experience.

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: 00:14:41

He's not panicking, but he's

paying very close attention.

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: 00:14:45

And that's my recommendation to you

guys is don't panic, but pay close

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: 00:14:49

attention to all this AI things.

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: 00:14:51

Start to integrate AI learning and

everything that you're doing on top

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: 00:14:54

of your data analytics learning.

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: 00:14:56

And that's something I'm gonna

be trying to do on this channel,

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: 00:14:58

specifically on my newsletter as well.

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: 00:15:00

I'm gonna start to try

to help you become an.

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: 00:15:02

AI native data analyst or

an AI fluent data analyst.

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: 00:15:06

So if that sounds interesting to you and

you actually want those tips delivered

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: 00:15:10

to your inbox every single week, you

can join 50,000 other aspiring data

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: 00:15:14

professionals@datacareerjumpstart.com

331

: 00:15:17

slash newsletter, and it's

absolutely free to join.

332

: 00:15:20

Guys, stay positive.

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: 00:15:21

Data jobs aren't dead.

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: 00:15:22

There's lots of data jobs left

and there will be in the future.

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: 00:15:25

That's my message to you and I

hope you take it to your heart.