From curious to career-ready: what went down at the Discover EngD event

You’re about to finish your Master’s. You’re curious, ambitious, and not ready to settle for a typical first job. That’s exactly the mindset that filled the halls (and TEAMS space) of JADS’ Discover EngD event this week. Held both online and in our historic building in ‘s-Hertogenbosch, this session gave future data scientists a raw, real look at the Engineering Doctorate (EngD) in Data Science — a two-year, salaried post-master’s program where you don’t just study data science. You do it.

Real questions, real stories, and real data science, straight from the people living it.

This isn’t another classroom degree. As an EngD trainee, you’re employed by TU Eindhoven, with full salary and benefits. You’re treated like a professional from day one, working on projects that deliver real value to real companies. It’s the kind of setup that lets you learn, grow, and contribute — without waiting four years for a PhD or jumping into the industry without a safety net.

What is an Engineering Doctorate in Data Science at JADS?:

“This program gave me a very nice experience so far.” — Tuğçe Meriç

Second-year trainee Tuğçe Meriç shared how she went from mastering mathematics in Turkey to tackling industrial projects in the Netherlands. Right now, she’s deep into her final project at ASML — helping them make black-box models understandable. “I’m not building a model from scratch,” she said. “I’m making an existing one explainable. They know it works — they just don’t know why it works. That’s where I come in.” Not sure if your math background stacks up?

“You don’t need to know everything,” Tuğçe reassured one participant. “What matters is that you can learn fast and think critically. That’s more useful than memorizing formulas.”

A global collision of perspectives

One of the things that stood out during the session? The diversity of the EngD community. Engineers, mathematicians, marketers, and AI grads — from Greece to Turkey to China. Everyone brings something unique to the table. It’s not just a cohort. It’s a global collision of perspectives. That kind of diversity isn’t just about flag-counting. It’s the fuel behind stronger collaboration, deeper problem-solving, and the kind of peer learning you don’t find in traditional programs.

“It’s like going from a 5-day sprint to a 3-month marathon.” — Niko Tsimpliaridis

For first-year trainee Niko Tsimpliaridis, the shift from the Data Challenge Week to real projects was intense — in the best way. “In the challenge week, we worked with Den Bosch FC on football strategy using player location data,” Niko explained. “It was fast, messy, fun. Then we jumped into our first real company project — three months of deep work with stakeholders who actually use your results.” And if you’re wondering what you need to prep?

“Don’t stress about mastering every tool. Just get comfortable with Python, learn to communicate clearly, and be ready to work in teams. The rest, you’ll pick up on the job.”

“We don’t want ‘teacher-student’. We want knowledge exchange.” — Francesco Romeo

The host, Francesco Romeo, kicked off the session with humor and honesty. “My job today is mostly to annoy the panel,” he joked, “but seriously — I’m here to show you what we’re really about.” Francesco, also a current trainee, made it clear that JADS isn’t a lecture-hall experience. “Our modules are short and intense. Our interactions are collaborative. We’re here to work alongside companies and solve their problems. That mindset shift — from classroom to client — is a big part of what makes this program special.”

 

“70% of my time is spent communicating. 30% coding.” — Alumnus Wenjun Liao

Wenjun Liao, EngD alumnus and now AI consultant in finance, returned to share what life looks like after JADS. “As a consultant, most of my job is translating business needs into data science problems. That means talking with people, aligning goals, building trust,” he said.

“You don’t just ship models — you make sure they’re useful, used, and maintained.”

And he didn’t stop at the job. “My final project was at a hospital — building a machine learning tool for pharmacists. After I graduated, they asked me to co-author a peer-reviewed paper. That wasn’t required — but it shows the level of work you’re doing here.”

EngD Alumnus Wenjun Liao, currently working as an AI Consultant at DLL

Got a Startup idea? JADS has your back

If your career goals involve launching something of your own, you’re in the right place. The JADS Playground is our in-house incubator for startups — helping trainees turn bold data science ideas into real ventures, with coaching, academic resources, and a community that knows what it takes to innovate.

What you need to apply to the EngD program in Data Science?

Think you’re a fit? Here’s what you need:

• A completed Master’s degree (in a relevant field)

• English proficiency (or proof you’ve studied in English)

• Most importantly: a clear motivation — why this program, and why now?

Applications go through a unique selection process, including the Data Challenge Week — our way of seeing how you work under pressure, in a team, solving real data problems. Throughout the event, one thing became clear: this program doesn’t just teach you data science — it puts you in the middle of it. You’re not solving textbook exercises. You’re designing explainable AI systems, optimizing supply chains, and making real impact from day one.

We closed the Discover EngD event with a tour, games, and drinks (of course)

After the Q&A, in-person attendees got a guided tour through our beautiful, quirky campus — a 140-year-old monastery turned data science hub. And because this is JADS, we didn’t end with a handshake. We ended with games, networking, and drinks.

✅ Ready to explore the EngD?

We’ll be sending out a follow-up email with slides, next steps, and application info. But if you already know you’re ready to explore a career built on data, design, and impact — check out the program now. This isn’t just a degree. It’s your launchpad.

Learn more or Run through the FAQ