Can Freshers Really Get Jobs in Data Science or Machine Learning? Here's What the Data (and Real Stories) Say

By: A Tech Education Enthusiast

If you’re a student or recent graduate wondering whether data science or machine learning is even possible as a career path straight out of college, you’re not alone.

It's a question I hear often:
“Do companies actually hire freshers for data roles?”
The short answer: Yes, but it depends on how you prepare.

The Myth of the "Experienced Fresher"

Data Science and ML roles often feel inaccessible because of the job listings we see online:

3+ years experience in Python, SQL, TensorFlow, PyTorch, Docker...
PhD preferred.
Publications in top AI conferences.

This can discourage students who are genuinely passionate but don’t come from elite academic backgrounds or who haven’t had access to world-class research labs.

But here’s the truth: You don’t need to be a PhD or Kaggle Grandmaster to get started. What you do need is exposure to real-world problems, not just course certificates.

Real Examples from the Ground

One recent example I’ve followed closely and noticed a few news articles mentioning from Newton School of Technology (NST) — an undergrad tech program in India focusing on CS, AI, and Data Science.

Rather than relying solely on lectures and exams, NST pushes students into projects, internships, and hackathons from year one. And the results speak volumes.

By the end of their second year, 93% of their AI/ML students had landed internships at notable companies like:

1. Razorpay – building internal AI tools for dev workflows.
2. DRDO (India’s Defence Research) – working on humanoid robot vision systems.
3. Sarvam AI – developing UI for clients like Swiggy, UIDAI, and Tata Capital.
4. Physics Wallah, Allen Digital, and Zoomcar

Some even had two internships before completing year two, something unheard of in most traditional colleges.

This tells us something very important: The pathway to early data careers exists, if the system you're in supports hands-on, outcomes-first learning.

So What Can You Do as a Fresher?

If your college doesn’t offer this kind of ecosystem, you can still build your own. Here’s how:

1. Start with Basics, but Apply Them

Don't get stuck in course loops. Start small:

1. Predict house prices with linear regression.
2. Run sentiment analysis on Reddit threads.
3. Build a recommendation engine using your Spotify history.

2. Open-Source > Certifications

A well-commented GitHub repo speaks louder than 10 Coursera badges.

3. Intern Early, and Often

Even unpaid or short-term projects matter. Look for:

1. Startups with small teams needing analytics.
2. NGOs or research labs looking for student contributors.
3. Local businesses open to data insights.
4. Follow the Right Titles

Jobs won’t always be called “Data Scientist.” Look for:

1. AI Intern
2. ML Engineer Trainee
3. Junior Analyst
4. Applied Research Intern

Don't Wait to Be "Job-Ready"

You don’t have to wait until your final year or complete a master’s to enter data science. Many of the most exciting roles now are open to people who:

1. Can learn fast
2. Can build small and iterate
3. Can explain what they’ve built

Whether it’s through new-age tech colleges like NST or your own self-driven path, opportunities for freshers in data science and ML are very real, if you're willing to put in the effort.

Let's Talk:
Have you landed (or are struggling to land) your first ML internship? Share your journey below, I’d love to learn from you or help if I can.