Anuj Tomar

Posted on Jul 10

“Data Science Is a Dead Career” — The Truth Behind the Trend No One Wants to Say Out Loud

It used to be the sexiest job of the 21st century. Now, people whisper that it’s over. What happened?

Let’s Get One Thing Straight: Data Science Isn’t Dying — It’s Splitting

I know you’ve seen the headlines:

“AI killed the data scientist.”
“Everyone’s using ChatGPT — why hire analysts?”
“No-code tools made data science obsolete.”

But here’s what’s actually happening:
Data science didn’t die. It broke apart.

And the generalist “do-it-all” data scientist?
That role is disappearing.

The Old Data Scientist Role Is Becoming Obsolete

From 2014 to 2020, companies hired “data scientists” to do everything:

Clean messy data
Build dashboards
Write machine learning models
Predict customer churn
Build PowerPoint decks for leadership

It was a golden era. If you knew Python, pandas, and a bit of SQL, you were in.

*But now?
*

AI tools do the boring stuff faster.
Business teams use self-serve dashboards.
And ML engineers have deeper specialization.

So the old “Swiss Army knife” data scientist?
Not needed anymore.

The Rise of “Unbundled Data Science” Jobs

In 2025, companies are hiring specialists, not generalists.

*Here’s how the role split:
*

Each role has its own stack, salary range, and learning curve.

If you’re still calling yourself a “Data Scientist,” you may be signaling that you’re stuck in 2018.

AI Has Changed the Game — But Not How You Think

Yes, AI can now:

Build Python scripts
Create SQL queries
Clean datasets
Generate charts
Even write reports

But that doesn’t mean the human is obsolete.

*Here’s what AI can’t (yet) do well:
*

Ask the right business question
Design the right experiment
Handle messy org politics
Balance ethics, privacy, and data use
Communicate trade-offs to non-technical execs

In short: AI can replace junior-level execution, but not senior-level thinking.

The Skills That Still Matter in 2025 (And Beyond)

To stay relevant — or break in — focus on roles, not hype.
Here’s what’s actually hiring right now:

✅** SQL Fluency**
Still the #1 skill for 90% of data jobs.
Not sexy, but powerful.

✅ Business Context
If you can tie metrics to money, you win.

✅ Communication
Can you tell a story with data in slides, not just code?

✅ Deployment & MLOps
If you’re into ML, learn how to ship models, not just train them.

✅ Data Engineering Literacy
Understand dbt, Airflow, cloud pipelines — or partner with those who do.

What to Call Yourself Instead of “Data Scientist”

Here’s what top companies are hiring for now:

Product Data Analyst
Analytics Engineer
Decision Scientist
Machine Learning Engineer
Quantitative Researcher
Marketing Analyst
Data Product Manager

Find the title that fits your interest + your skill set.

“Data Scientist” is now just a vague label.

Final Thought: The Title Is Dead, But the Career Isn’t
The world runs on data. Always has, always will.
But the people who succeed in 2025 and beyond?

They won’t chase the title.
They’ll chase impact.

You’re not here to write perfect Python.
You’re here to help your company make better decisions.

So stop worrying if “data science is dead.”
And start figuring out where you actually want to play in the stack.

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