Introduction

As data science becomes increasingly central to solving real-world problems, its role in academia is growing just as fast. From developing new algorithms to applying machine learning in interdisciplinary research, the academic path in data science offers more than just theory - it brings innovation, impact, and hands-on exploration. To delve deeper into this evolving field, we conducted an interviewed with Ana Yoon Faria de Lima, a Master's student in Computer Science at ETH Zürich and Research Assistant at KOF Swiss Economic Institute. Her journey offers a valuable glimpse into how data science can be explored through academic studies, hands-on research, and real-world industry experience.

From Uncertainty to Innovation: Ana's Path into Data Science

Ana Yoon Faria de Lima didn’t set out knowing she’d pursue data science - it was a path she discovered gradually.

Like many students at the beginning of their academic journey, she started by watching "careers of the future" videos. It was there that she first encountered the world of computer science and engineering - fields that stood out to her as both exciting and impactful.

That initial curiosity led her to pursue a degree in computer science in Brazil.

"In my first year, I realized I had a strong interest in the financial market - and as I dove deeper, I discovered how exciting data science could be within that context.

I did a summer internship in database management for the banking sector - it brought together everything I was interested in: finance, software engineering and data analytics.”

This early combination of interests shaped Ana's journey. In her second year, she became the financial market lead in her university's extension group. A six-month internship in another bank followed, which she loved. But instead of continuing immediately in the corporate world, she pivoted to something more exploratory: a 1.5-year research project in data science.

"What really pulled me into research was the need for deeper knowledge. In software engineering, you can often find answers quickly online. But in data science, it’s more complex—you need to understand the foundations."

During her research phase, Ana received a lab scholarship that took her abroad. She spent time at the Eindhoven University of Technology in the Netherlands, working with a tech innovation group. There, she conducted research full-time alongside PhD students.

Now, she is pursuing her Master's in Computer Science at ETH Zürich, specializing in artificial intelligence, and working as a Research Assistant at KOF Swiss Economic Institute.

The ETH Zürich Experience

ETH Zürich is considered one of the most prestigious technical universities in the world, and Ana's journey there wasn’t without preparation. Her application stood out thanks to a deeply considered motivation letter.

"I wrote my motivation letter a few months before the deadline. I think what matters most is showing your purpose - why you want to study there. They look at your academic record and ranking, but also - they care about what you're doing beyond just studying."

Ana also appreciated the flexibility of ETH’s curriculum, which allows students to personalize their academic paths to suit both theoretical and practical interests.

"It’s technical, but it doesn’t have to be purely theoretical. You can shape it depending on what you want to explore."

Data Science in Action: Real-World Impact

Currently, Ana is working on a recruitment platform project focused on analyzing patterns in hiring. Her role involves preprocessing large datasets using Polars, a Python library built on Rust for performance.

Her experience in applied research also includes a standout project she conducted earlier during her academic journey. While on a research scholarship at Eindhoven University of Technology, Ana collaborated with Eindhoven City Hall on a data-driven public policy initiative.

"We analyzed a cycling policy. I worked as a product owner and also handled data science tasks, like analyzing user data and presenting results to an ethics committee. It was an incredible interdisciplinary experience."

Working alongside policymakers, cycling activists, and tech experts, Ana gained firsthand experience with the kind of cross-sector collaboration that modern data science increasingly requires.

Trends to Watch: AI Specialization and Chatbots

When asked about the most exciting trends in AI and ML today, Ana pointed to two areas:

• The growing specialization in AI degrees, which is transforming how people approach education and job roles.

• The proliferation of chatbots, which she sees becoming an even more integral part of everyday digital interactions.

We also asked Ana what she thinks about the recent popularity of AI-assisted coding tools like vibe coding:

"Vibe coding is great for speeding up your work, but I wouldn’t recommend it for beginners. You need to know how to code first—understanding what you're doing is essential."

The Power of Trying: Advice for Aspiring Data Scientists

Ana believes the early stages of your career should be a time for exploration:

"My biggest advice is: switch as much as you want. Your bachelor’s is your moment to try everything - research, big companies, startups, hackathons, different courses. It’s the best way to learn."

One experience that shaped her perspective was participating in multiple hackathons, which gave her insights into real-world problem-solving and fast-paced collaboration.

"Hackathons helped me see how data science is applied outside the classroom. They're inspiring, hands-on, and give you a taste of what working on real problems feels like."

Ana’s story is a great example of what happens when curiosity meets courage. Her academic journey and hands-on experience reflect a powerful combination of technical skill, interdisciplinary thinking, and a passion for using data to make a difference.