Is the AI and Knowledge Job Market Useless?

knowledge science was dying 7 months in the past?

It was additionally dying 2 years in the past. 

And dying 3 years in the past.

And to not point out it was additionally dying 5 years in the past.

Nonetheless, from the place I stand, that is undoubtedly not the case. Folks nonetheless appear to land knowledge scientist jobs.

I imply, I actually assist folks do that each week in my teaching programme.

So, what on earth is happening?

Properly, on this article, I wish to break down:

• What the present knowledge market appears like
• What it truly means to be a knowledge scientist
• And, what you need to be doing to land a job on this present local weather

Let’s get into it!

Market Outlook

As lots of you’ll know, there have been important layoffs throughout 2022 and 2023, with almost 90,000 tech workers being laid off in January 2023 alone.

In actual fact, it was so extreme that TechCrunch even created an archive of all of the layoffs that occurred throughout this era!

Nonetheless, in line with a examine by 365datascience, knowledge jobs weren’t that affected by these layoffs; they discovered that:

Apparently, our pattern’s largest group of laid-off workers didn’t maintain tech jobs — 27.8% labored in HR & Expertise Sourcing, whereas software program engineers got here in second with 22.1%. Advertising workers adopted them with 7.1%, customer support with 4.6%, PR, communications & technique with 4.4%, and many others.

For instance, solely 2.7% of individuals laid off from Amazon throughout this era had the title of knowledge scientist.

In response to one other examine:

Knowledge science job postings grew 130% yr over yr after hitting all-time low in July 2023, whereas knowledge analyst openings grew 63% in the identical time interval.

And we will additionally see that the wage of knowledge jobs as a complete has been rising through the years.

So, it’s clear that knowledge science will not be dying in anyway; if something, it’s rising.

Nonetheless, why does it really feel very arduous to get a knowledge scientist job proper now, particularly on the entry and junior ranges?

To elucidate that, we have to look previous the numbers and actually perceive what the trendy knowledge scientist is.

Knowledge Science Evolution

As an insider on this discipline, let me let you know a secret.

Knowledge science will not be dying; it’s evolving.

10 years in the past, corporations would rent knowledge scientists to tinker with machine studying fashions in Jupyter Notebooks.

In actual fact, that is precisely what my first knowledge science job was like.

A knowledge scientist was like a Swiss Military Knife — one individual anticipated to do all the things from cleansing knowledge to constructing fashions and presenting to the CEO.

Nonetheless, over time, corporations realised they have been getting no return on funding from this technique, in order that they grew to become extra stringent about roles and obligations to make sure they weren’t losing their cash.

This has led the information science job to develop into fragmented, and the title has develop into meaningless, as you can see knowledge scientists doing fully totally different jobs at totally different corporations.

Usually, three flavours of knowledge scientists exist right this moment.

Analyst

This kind of knowledge scientist is intently aligned with the enterprise aspect and primarily focuses on reporting workflows and experimentation.

For instance, you’ll:

• Get knowledge from an organization database or different sources.
• Write some code that may be very linear and bespoke by nature, beginning with ingesting knowledge, cleansing it a bit, then performing some EDA and a few inferential or fundamental modelling work.
• As soon as full, you set collectively a report that particulars the evaluation, gives visualisations and different metrics, and gives a suggestion based mostly on the evaluation’s objectives.

This kind of knowledge scientist is extra of a knowledge analyst and sometimes requires extra enterprise area information.

Engineering

The main target of any such knowledge scientist is on constructing and deploying options. This is usually a vary of issues like:

• Inner software program tooling
• Machine studying fashions that drive choice making
• Constructing libraries

This position leans extra towards software program engineering, however in contrast to a software program engineer, it requires higher information of maths, machine studying, and statistics.

These days, any such job has moved past the “knowledge scientist” title and is now known as a machine studying engineer.

This isn’t entry degree place, and usually requires 2–3 years expertise in an adjoining position like a software program engineer or analyst first. So many graduates and other people with little expertise would battle to interrupt into this particular knowledge science place.

Infrastructure

This kind of knowledge scientist is the rarest, primarily as a result of it has its personal title: knowledge engineer.

The purpose of this position is to construct the information infrastructure and pipelines to deal with the enterprise’s knowledge. This knowledge is then used downstream by machine studying engineers, analysts and even non-technical stakeholders.

This position has develop into more and more necessary, particularly with the emergence of generative AI in recent times, which requires the power to successfully retailer giant quantities of knowledge and stream it with low latency.

At some corporations, you may additionally be an analytics engineer, which is a extra business-focused knowledge engineer.

I do know, so many titles, its arduous to maintain up!

Junior vs Senior

A examine printed in September 2025 has been making fairly a couple of waves within the knowledge and machine studying house.

The examine examined 285,000 corporations between 2015 and 2025 and the way their adoption of GenAI has affected their hiring processes for junior and senior positions.

Notice: this is applicable not simply to knowledge scientist jobs however to all jobs at these corporations.

You may see within the plot beneath that hiring for senior positions continues to be growing, whereas hiring for junior positions is lowering.

This makes intuitive sense, as juniors’ obligations are seemingly simpler to automate with AI than seniors’ because of the wealth of expertise they’ve constructed through the years.

What I wish to clarify, although, is that corporations aren’t making juniors redundant nor are there no extra junior positions left available on the market. 

Most individuals will have a look at this graph and assume that the junior knowledge science market is turning into extinct. However that’s objectively not the case.

Hiring continues to be occurring, however the price of recent positions being posted will not be growing. The availability curve stays unchanged whereas demand stays excessive. 

That’s why it feels so arduous to get an entry-level job these days.

What Can You Do?

I’m going to be trustworthy, it’s turning into extra aggressive to interrupt into knowledge science, nevertheless it’s not inconceivable.

Gone are the times when all you wanted was fundamental Python and SQL, and having carried out Andrew Ng’s Machine Studying course.

These are issues everybody has these days, so it’s worthwhile to go the additional mile and differentiate your self greater than you used to.

There are a lot of methods of doing this, for instance, you undertake and specialize in sure technical domains like:

• GenAI
• Mannequin deployment
• Time sequence forecasting
• Suggestion techniques
• Area-specific experience

Specialists are arguably turning into extra necessary as information is more and more democratised by AI. Having deep experience is nearly a rarity these days.

Another choice is to go for a lower-level place, like a enterprise or knowledge analyst position, that’s extra pleasant to junior and entry-level positions, after which slowly construct your means as much as a full-time knowledge scientist place.

You also needs to concentrate on areas that AI can’t actually exchange:

• Speaking successfully with totally different audiences
• Understanding the enterprise influence of your work
• Essential considering and realizing what drawback to resolve
• Sturdy fundamentals in maths and statistics
• Relationships and community

These are timeless abilities, particularly the final one.

You might need heard the saying:

It’s not what you understand, however who you know

I truly disagree with this.

The actual energy is in who is aware of you.

When you’ve got a strong community and relationship with many individuals within the discipline who worth and belief you, you may faucet into this to get referrals, alternatives, and even increase your community additional.

The leverage this gives is unbelievable. I at all times inform my teaching shoppers that referrals and networks are actually the golden ticket to getting top-end knowledge science jobs.

And all it requires, is simply effort and pushing your self out of your consolation zone to talk to folks you wish to join with.

Applied sciences will come and go, however precise human relationships will stay central on your complete profession.

The reality is, you’re going to must reinvent your self each 3–5 years as a knowledge scientist, since know-how shifts in a short time.

So asking “Is knowledge science dying?” misses the purpose.

Knowledge science is at all times technically dying because it’s constantly evolving and remodeling.

However that’s what makes it thrilling.

And if you’re prepared to up-skill and put in additional effort than others, you’ll be rewarded very nicely.

Should you’re able to dive into knowledge science after studying this, that’s an important first step. 

However right here’s the truth: I’ve been on this discipline for 5 years, and searching again, I spent my total first yr on duties that have been an entire waste of time. In right this moment’s hyper-competitive market, you don’t have the luxurious of trial and error.

To keep away from my errors and speed-run your progress, take a look at this information the place I map out precisely how I’d develop into a knowledge scientist once more.