The Digital Engineers of Nitor: Jukka found his way to data science through brain and AI research and relishes in uncovering insights from data

Hi Jukka! To start, could you tell us a bit about your career background and how you ended up at Nitor?

I graduated with a master’s degree in cognitive science from the University of Helsinki. While studying, I worked as a research assistant in brain research projects, which sparked my interest in data and how it could be applied. I found analysing brain research data and applying algorithms to it exceptionally fascinating.

After earning my master’s, I went on to write my doctoral dissertation in computer science, researching both generative AI and language generation. This was back when AI wasn’t as popular as it is today.

I worked at the university until 2016, when I received my PhD. At that point it was time to start pondering my next career move, and after a few twists and turns, I ended up at Nitor. That was in 2019, so I’ve been here for quite a while.

The work of a Data Scientist is very diverse. What does a typical work week look like for you?

Variation is part and parcel of the job description and its environment. I work closely with my client’s key business individuals alongside other data experts. Our efforts include exploring which projects to start development on next, while looking for ways to garner more insight of the business environment through data.

Another example would be working with machine learning models. My current client is a telecommunications company, and we’ve developed models such as ones that can recommend the most suitable mobile subscription for an individual. Such machine learning models require continuous development, which means we are continually enhancing them with new data sources and responding to evolving business needs and environments.

As technology tends to advance in leaps and bounds, often my work also involves investigating and taking new tools into use. That also means further development on models and processes to ensure everything runs smoothly with the latest tools.

Sounds interesting – and challenging. How has your work changed over the five years you've been at Nitor?

Data science is indeed a broad field, and depending on one’s role and the client's industry, it can cover a lot of ground. The core of my work consists of machine learning, analytics, and data management, of course. I also work on data pipelines and infrastructure.

When I started at Nitor, the data science field was much less mature than it is today. Companies would sometimes hire Data Scientists without really knowing what kind of state their data was in, or what actionable insights they were looking to uncover. Companies have better data management practices today, but more importantly, businesses understand the link between high-quality data and its financial value.

Jukka is a valued and trusted team member in the customer team; deep understanding in the field of data science and the ability to very efficiently solve the technical challenges we face. Always willing to help and a can-do attitude is what we, and our clients, truly appreciate.

- Sami Airaksinen, Senior Software Architect

You surely have tried-and-true methods in your toolkit when starting on a new client project. How do you kick off a data project?

The first step is understanding the context. The best people to clarify the big picture are the people on the client side who are most versed in the ins and outs of the business. The first steps should include determining what kinds of business-related challenges are data-oriented and what kinds of solutions we should be looking for. Only then can we start working on tasks like modelling and building automated processes.

There is a strong research component embedded in my work, as a central part of data science involves uncovering insights from the available data. Not only does this provide valuable benefits for my clients, but it also brings me intellectual joy. That’s the most rewarding aspect of my job.

Brilliant! So, tell us, what qualities make up a Nitor Digital Engineer?

Generally speaking, I’d say that what unites Nitoreans is a passion for the industry and a particular intellectual curiosity. Nitoreans tend to be a humble and very pragmatic bunch. We steer away from getting hung up on things that don’t advance the project or benefit the client. 

Nitor’s Digital Engineers approach things with enthusiasm, care deeply about the substance of their work, and are always eager to learn. This, in turn, drives us to pursue solutions of the highest quality. Curiosity and passion are essential building blocks of that mindset.

Well said. Speaking of these qualities: in your video feature, you discuss working on a system for managing aircraft landing times. What’s that about?

Some time ago, a couple of my colleagues and I worked on a project with Finnair to create a system that predicts the costs of potential flight delays. The system uses AI to calculate the domino effect of a flight delay, such as how it might affect departure times for connecting flights, disrupt logistics, and increase costs.

Sounds like a rewarding project. Finally, how does an experienced Data Scientist like yourself unwind after work?

We have two small children, so much of my free time is spent with the family. I also enjoy endurance sports, which is a great way to clear my mind. I’ve also played classical guitar for a long time and music is very close to my heart. My oldest child recently started studying music, which has brought back warm memories of my own music academy days.

So there’s warmth, creativity, and resilience-building even in your spare time. You sound like a true Digital Engineer. Thank you, Jukka!

Thank you!

In this campaign, we’ll introduce Nitoreans in different roles. Every Nitorean is a Digital Engineer: a pragmatic and solution-oriented helper who doesn’t settle for assumptions. Instead, they take one step further to seek the right questions and even better answers.