»It’s my personal driver to push the boundaries of what’s possible«

Data Manager Mathias Engel is not your typical IT consultant. He holds a degree in physics and has formerly worked as a statistician in a group of leading cancer researchers. Today he uses his scientific skill set leading Netcompany projects involving advanced machine learning, data testing, and analysis.

 

Can you sell noodles at McDonald’s? they once asked themselves at the fast food chain in South Korea.

An employee had an idea. They could buy a bunch of big pots, stock up on a variety of flavoured noodles, and then test it out at a couple of restaurants. But then someone else chimed in with a twist: »I can do it for just €10, all I need is a marker and a sign. We’ll slap ‘noodles’ on the menu and see if anyone orders. If they do, we’ll just tell them we’re sold out,« Mathias Engel says paraphrasing a story he recently heard.

»The first approach is thoughtful, structured, and methodical. The second? A scrappy shortcut straight to the answer. And that’s the kind of thinking I’m chasing in my work–creatively hacking your way to clarity.«

For the past six years, Mathias Engel has combined such a structured, methodical approach with creative problem-solving to drive projects involving advanced machine learning at Netcompany. But this wasn’t exactly a preordained position.

The 34-year-old holds a degree in physics and prior to starting at Netcompany he spent five years with a group of experts researching cancer and systems biology on a track to a position among leading scientists.

Today he might have hung his lab coat, entering the world of IT, but at the heart of his work is still experimenting. And by creating small ‘research teams’ within his projects, he’s testing hypotheses to quickly determine what can and should be built for a client.

»When I started studying physics, my focus was on the non-living world, so to speak. Then I shifted to biological systems, and today I work with human systems at Netcompany,« Mathias says reflecting upon his career crossover. But throughout the journey, the motivation has been the same.

»I need this overarching purpose in what I do—it’s what keeps me inspired.«

The right path isn’t always a straight line. We often navigate twists and turns, gaining new perspectives that shape our destinations along the way. In this series you’ll meet some of the Netcompany talents that have transitioned into the world of IT, bringing diverse skills and viewpoints to the company.

The little inventor

 

Mathias Engel has been fascinated with experiments and problem solving for as long as he can remember. His mom used to call him ‘the little inventor’ as he would spend countless hours building with LEGO, or experimenting with pipes, balloons, and air pressure. And when a school teacher one day tapped him on the shoulder urging him to follow a path in physics, that’s what he did.  

»I’ve always been drawn to the fundamental questions of the world of physics–problems so vast that you can’t simply think your way to the solution. Many thinkof physics as a lot of equations on a blackboard. But in reality, it’s all about figuring out how to design and conduct experiments, and I love this disciplined or principled way of working.« 

At university, Mathias Engel initially explored high-energy and theoretical physics but soon realised that excelling in these demanding fields required being among the top 10%—a level he didn’t aspire to. Instead, he ignited a passion for modelling biological systems, ultimately leading him to a role as an in-house statistician and machine learning expert in a small science group researching cancer treatment. 

»It was an amazing time that taught me more than my physics studies ever did,«Mathias Engel says. »The team consisted of five biologists, incredibly sharp minds, and an ambitious lead who aspired for us to be the best in the world. They were ready to skip Christmas Eve if their cell experiment was developing«.  

‘Hey Mathias, there are 100,000 new cell images on the server. Can you take a look at them?’ they would say, and then he would dive in, train machine learning models, and run analyses of the complex image and DNA data.  

»That’s where I learned to process massive datasets and developed the data skills I’ve brought with me into Netcompany.«

Catching talent by the tie

 

In 2018, the research group disbanded, marking Mathias Engel’s unexpected entry into the IT world. A Netcompany employee approached him figuratively asking if he would mind wearing a suit on a daily basis? And no, he wouldn’t. 

»I was already rocking that researcher look with a blazer, corduroy shirt, and a loose tie, so it didn’t feel like a big change,« he says with a smile, and three days later, he had his first day in Netcompany, ascribed to a project with The Danish Ministry of Taxation, an »excellent school for learning the basics as a data consultant«.  

»I’d been a self-taught programmer up until then, but here I learnt the theory behind the field. It felt like I’d landed somewhere that truly appreciated my skills, but what I didn’t expect to enjoy this much was speaking with clients, the whole role of being a helper«.

Today, Mathias oversees the majority of Netcompany’s AI and machine learning projects, both in Denmark and internationally. His journey has included defining the future AI strategy for a major Nordic retailer by developing algorithms transforming the company’s approach to data and automation. He has played a key role in crafting AI solutions across the Danish public sector. And during the COVID-19 pandemic, he contributed to the UK healthcare system by designing machine learning models to support critical decision-making.

These days, Mathias is leading Netcompany’s most ambitious AI project yet, working with his team to support the Danish State Railways, DSB, in improving operations and enhancing public mobility. 

»I love to be in that small niche within Netcompany working with advanced analytics and hypothesis testing. It lets me draw not only on my technical expertise but also on my experience collaborating with people outside my field,«he says.

Pushing boundaries

 

Most clients need structured data first, Mathias Engel explains. Once that’s sorted they can look into extracting more value from that data, and only then they might address the possibilities of AI and machine learning.   

»It’s only 1 out of 10 AI projects that actually materialises, so I work with proof of concept to demonstrate whether an idea or concept has real, practical potential,« he says, explaining how a skilled team will be able to determine if the available data has the ‘signal’ needed for the desired purpose in weeks instead of years. 

»With DSB, we’ve been hacking away to figure out how to create the best model for predicting train schedules–and we’ve had an absolute blast doing it,« he says continuing:   

»It’s all about being able to test a hypothesis quickly and efficiently, and what I find fascinating is the chance to discover and develop something new«.  

Discovering a research result, though, is one thing, but applying it is often much harder.  

»You might find a cure for cancer in an experiment relatively quickly, but turning it into a pill can take 12 years. The same applies to our projects. But it’s my personal driver to push the boundaries of what’s possible—and to do it in a way that continues to create value.« 

Uncovering the visions that drive a project forward is exactly what keeps him motivated.  With the Danish tax authorities, for instance, there was a glaring issue of people not paying their taxes, and fuelled by this sense of unfairness, he developed an algorithm to identify errors.

The same sense of purpose applies to his current project with DSB.  Predicting train arrivals and departures ensures commuters can confidently plan their day and spend time on what matters most to them, and this may encourage more people to choose public transport, with a positive impact on the climate, he explains.  

»All of this makes sense to me. And I need this overarching purpose in what I do–it’s what keeps me inspired«.

Data as the new oil

 

Mathias Engel finds himself on the cusp of being a digital native. He remembers the cumbersome process of booting up a computer and the scratchy sound of the modem connecting to the internet through the phone line, and for the past 12 years he’s been delving into AI and machine learning. 

During that time, he has witnessed more than one hype wave, he says, from self taught AI models beating humans at complex games to the sudden ability to use image recognition for diagnosing skin cancer. While we’re currently riding the biggest wave to date–kickstarted by ChatGPT–Mathias is already looking ahead. 

»Having advanced language models, capable of handling all the tedious tasks we don’t want to do, is great. But it’s meaningless if you don’t have control over the data you’re feeding them. Going forward I think the idea of data being the new oil holds more truth than ever,« he says continuing:  

»Companies will increasingly realise that the real value doesn’t lie in the AI model itself, but in their own data. Sure, we can generate text, images, and sound, but next up is how to handle this responsibly and securely«. 

Today he’s the dad of a 2 year old daughter, who might be called an AI native, experiencing far fewer barriers when it comes to interacting with computers. But what exactly does he see when looking into the crystal ball? 

For a long time Apple has managed to dominate the market with a number of highly successful solutions and devices. When they introduced Siri, though, it didn’t really catch on, he says, explaining how the new Siri combined with ChatGPT will change the game.  

»My daughter will grow up speaking way more with her devices and likely be more reactive than proactive. Perhaps she will even experience thought-to-action technology«.

The groundwork for the groove

 

When Mathias Engel isn’t leading complex AI projects at Netcompany, he enjoys smashing a drumset. Growing up with a jazz-musician father, he developed a deep love for rhythm, creativity, and dedication—values that also shape his work today. 

Despite his relaxed and humble manner, his success is far from effortless. Like music, it’s built on dedication and hard work. And to this day, music is more than a pastime—it’s a philosophy, balancing mastery, creativity, and discovery. 

»I started practicing jazz because of my dad. I spent hours perfecting my craft—later playing blues in rough pubs, diving into Latin beats with percussion, and now I’m exploring techno,« Mathias Engel says with a smile. 

Innovation, like music, requires mastering the basics before improvising. People see the final performance—not the hours of practice. 

»It’s fascinating how, even after a mentally exhausting day, there’s still a part of my brain that’s ready to create. It’s not a conscious process; it’s more like connecting with something deeper and subconscious.« 

This creative mindset mirrors his approach to solving problems. 

»Good experimentation requires creativity. You have to allow yourself to think differently—to play, to test, to explore. Just like in music, the best ideas often come from a sense of curiosity and fun«.