Data Science Day Interviews: Reaktor

Krapula-Ahti 2018-02-06 3 min read

Tyyppiarvon Data Science -päivä -haastattelusarja julkaistaan poikkeuksellisesti englanniksi, sillä itse tapahtuma on englanninkielinen.

”Data Science Day Interviews” -series introduces the main partners of Data Science Day. Now we introduce Jaakko Särelä, PhD, who  is AI designer and Principal consultant at Reaktor.

Tell briefly about yourself and how you ended up working for Reaktor.

I have worked on artificial intelligence and machine learning for almost 25 years, half of it in the academic world, and the other half in the private sector as a serial entrepreneur. For the last four years, I have worked at Reaktor, where I’ve been offered a very supportive culture in which to deepen my skills and widen my understanding of several different industries.

Why do you work in Reaktor and what is the role of Statistics / Data Science in your company?

Reaktor gives me a unique opportunity to see a wide array of projects, ranging from service design for some of the world’s leading media companies to building autonomous ferries on the bleeding edge of AI. My role as an AI designer is to understand the customers’ businesses, and design solutions that use AI or machine learning to solve their problems. At Reaktor some of our core competencies include statistics, data science and artificial intelligence, and we combine these with our software, design and strategy skills to create digital services for our clients.

Which tasks does your role include?  Which statistical methods and programs do you use in your job?

I design digital AI and data science services and products for our clients, and participate in their implementation together with our developers. I mainly use Python, R, and Stan. Bayesian methods and deep learning constitute the core of the methods I use.

Name three skills that you consider most important in your job.

First, communication: A data scientist never works in a vacuum, and our work is always connected to the business of the company as a whole. Second, critical thinking, since building valuable AI solutions often requires looking beyond the problems and solutions that seem evident; and finally, perseverance, since all success requires a lot of work and learning from past experience.

Are there any positions for students on your department and what kind of assignments students and new employees typically get to do? (If yes, you can also tell how students can apply for these jobs)

We constantly hire people with knowledge of artificial intelligence, machine learning and data engineering. You can apply at

If you’re still concentrating on your studies and not yet looking for a full-time position, we’re also hiring summer interns: you’ll find the details at Please note that the intern positions require proficiency in Finnish.

Which hints would you give to a young statistician who is aiming to work on your field?

Work to solve real problems, not just school assignments; work together to learn from others.