From Fluid Dynamics to Data Science Leadership: Education, AI, and Career Building in Tech

14.08.2025, 12:30
with Ekaterina Butyugina & Greg Tomasik

 

Hi Ekaterina, you’ve had a remarkable journey from academic research in fluid dynamics
to leading data science programs at Constructor Academy. What inspired you to move
into tech education – and what drives you most in your role today?

After completing my PhD, I wanted to transition from academia to industry and still stay close to my passion - Science. That’s when I discovered data science and the amazing opportunities it offers. I took a Data Science course back in 2019, and it completely changed my life. I fell in love with the field, and it has opened  many doors for me. The thrill of transforming raw data into powerful insights that solve real-world problems is simply unmatched. I feel empowered to be able to handle these complex challenges and help shape the future of this rapidly evolving field.

I want to show this world to as many people as I can, and help more people discover the power and beauty of data and AI.  That’s why I decided to stay with my incredible team: first as a teaching assistant, then as a consultant, and now I lead the program. I got to do exactly what I was hoping for — helping others find their own way into data in Switzerland. And when I see the success of my students, I know I have made the right decision.

 

Many of your students come from very diverse professional backgrounds. In your view,
what distinguishes those who successfully transition into Data Science or Software
Development?

Curiosity, persistence, and hard work - that’s what matters..The most successful graduates have a profound curiosity to learn, strong analytical thinking and resilience when facing challenges. They don't just learn the material; they actively apply it to personal projects that genuinely excites them. This innate drive to continuously build and solve problems is the true key to their successful transition into Data Science or Software Development.

We’ve had a philosopher, a journalist, and a schoolteacher all successfully transitioning into data science. Some of them wrote their very first line of code while preparing for our technical interview - and now they’re working at world renown companies like Google. Some of our students even return to their industry with renewed vigour and inspiration transitioning into a tech career. We see equally impressive transformations in our Full-Stack program as well.

All of this shows that the biggest barriers often exist in our own minds, and if you have a dream, you should follow it.

 

You’re a woman with a strong tech background yourself. How do you perceive the role
and visibility of women in Data Science and AI today – and what has changed over the
past 5 years?

That’s an interesting question - because in my immediate environment, I’m actually surrounded by amazing women, many of them in STEM. So for me, seeing women in Data Science and AI feels completely normal.

But looking at the broader picture, I’ve definitely seen progress over the past five years. More women are entering the tech field, and their achievements are becoming more visible and recognised. And this matters, because as they say, you can’t be what you can’t see.

That said, there’s still a long way to go - especially when it comes to leadership roles, conference stages, and influencing strategic decisions in AI.

What has changed is that the conversation is happening. Companies are more aware, and communities like “WiDS (Women in Data Science)”, “HerHack” or “Hello 50:50 World” are creating spaces where women feel seen, heard and supported. I particularly appreciate initiatives like women-focused hiring events and benefits such as extended maternity leave - that sends a strong message that inclusion matters. At Constructor Academy, we also offer financing options specifically to support women entering tech. 

Ultimately, we all have a role to play. It’s not just about women supporting women - it’s about building inclusive teams, cultures, and opportunities across the board.

 

You teach tools such as Python, SQL, Git, Docker, React, and various machine learning
frameworks. Which technologies and skills should newcomers focus on today to stay
relevant and connected to the market?

Generative AI is transforming the tech landscape, so for newcomers, a strong foundational understanding of AI is essential (LLMs, prompt engineering). I recommend starting with core machine learning concepts, then diving into applied topics like Retrieval-Augmented Generation (RAG), vector databases, agentic AI workflows, and tools like LangChain or LlamaIndex.

In parallel, cloud skills are becoming important - especially on platforms like AWS, Azure, and Google Cloud. Choose one and study. Most companies today expect data and AI professionals to know how to deploy, scale, and monitor solutions in the cloud. These skills are particularly in demand in finance, healthcare, and enterprise software sectors here in Switzerland.

Of course, the timeless essentials: SQL is always in demand. Python continues to be the dominant language for AI and data science. MLOps tools like Git, Docker, and MLflow are important for building scalable, production-ready systems.

And finally, soft skills matter more than ever. Technology evolves quickly, but an agile mindset, communication skills, and a willingness to learn will help you to adapt especially in the Swiss job market, where collaboration across teams, languages, and disciplines is part of daily life. According to the WEF2025 it’s clear that employers want strong analytical thinking, resilience and flexibility in this fast evolving environment.

 

What kind of feedback do you receive from employers regarding your graduates – what
do they particularly value? And are there any skills that are requested more often than
expected?

We work very closely with major and mid-sized international and Swiss companies. Many of our 1500+ Alumni work in these organisations so we get very candid feedback.  I recently received feedback from one of the major Swiss companies saying that having a Constructor Academy qualification is starting to become a big plus on a candidate’s CV. This  made me incredibly proud — of our programs, our team, and especially our graduates.

Employers tell us they appreciate our industry-oriented approach. Our training is hands-on and practical: students work on real-life challenges with real company data. That means they already have relevant project experience before they even step into their first job interview.

Another advantage is our willingness to teach the most current tools and techniques — not just the classics, but also the latest in Generative AI, MLOps, etc. We excel in being in touch and adapting to this continuously changing environment.

We teach our students to work both independently and as part of a team. By the end of the program, they’ve become what I like to call “universal soldiers” — agile, fearless, and ready to take on anything the tech world throws at them.

 

The conversation around salary transparency is gaining momentum in Switzerland.
What’s your personal take on greater openness around salaries in tech roles?

I believe greater salary transparency is a positive and necessary step — especially in tech, where roles and responsibilities can vary so much. Openness helps to create a more level playing field, reduces bias, and gives both employees and employers a clearer sense of market expectations.

That said, I also understand the hesitation some companies have, particularly in Switzerland, where privacy is culturally valued and compensation structures can be quite complex. But I think the trend is moving in the right direction. It can start with salary bands or published ranges, which already make a big difference in fairness and negotiation.

For junior professionals, underrepresented groups or career changers, this kind of clarity is especially important. It helps them make informed decisions and ensures they aren’t underselling themselves simply due to lack of experience or access to insider knowledge.

In the end, transparency builds trust — and trust is good for everyone.

 

If you were to reskill or change direction today – which tech field would you choose, and why? 

I’m happy where I am right now — I get to stay hands-on, work closely with people, and keep learning every day. 

But if I were to reskill or shift direction, I’d go deeper into AI — specifically, into developing new algorithms or tools that help automate repetitive or time-consuming processes. I’m fascinated by the idea of using AI to free other people (and myself) from boring, manual tasks so they can focus on more meaningful, creative, or human aspects of their work.

 

Finally, what advice would you give to individuals looking to launch or relaunch their
careers in the Swiss tech ecosystem – whether they are beginners or career changers?
Technically, strategically, or personally? 

My main advice is: get your foot in the door - any way you can. Whether it’s through internships, volunteering, contributing to open-source projects, or enrolling in hands-on education programs, the goal is to start building real experience and connections in the industry.

Also, don’t get discouraged by rejection. Sending out 100 applications is completely normal. I often suggest a 30-30-30 strategy: 30% blind applications, 30% through networking events, and 30% via personal connections like friends and family. The remaining 10%? Keep for wild ideas - like reaching out directly to someone you admire.

The Swiss tech ecosystem values continuous learning, so keep exploring new tools, stay curious, and focus not only on hard skills like coding or AI, but also on communication, adaptability, and collaboration.  Actively build your professional presence by attending relevant networking events. This is vital in Switzerland, where a high percentage (78%) of roles are filled through informal networks and personal connections. Building these relationships takes time, so be persistent and don't be disheartened.

 

Thank you very much, Ekaterina, for your valuable insights! We wish you all the best for the future.

 

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Dr. Ekaterina Butyugina, Program Manager and Data Science Instructor at Constructor Academy Zurich, combines a PhD in fluid dynamics with expertise in AI to guide professionals from all backgrounds toward successful tech careers.

 

 

Greg Tomasik, Co-Founder & CTO at SwissDevJobs.ch, GermanTechJobs.de & DevITjobs.uk. A Software Engineer with over 8 years of experience working at international companies. Involved in the recruiting industry since 2018, focusing on building transparent job boards for tech talents.