ArticleFebruary 23, 2022 · 4 min read time
Senior Data Scientist Eero Lihavainen is inspired by problem solving, learning new things and the opportunity to genuinely help customers. How did a tech student enthusiastic about music end up at Nitor as a digital engineer?
Eero, where does your interest in data science stem from?
I've always been interested in problem solving. My favourite subjects at school were math and languages. From a young age, I was interested in computers: one of my earliest childhood memories is the blue screen of the Commodore 64, the interpreter of the BASIC programming language. Of course, I used the computer for playing games, but later also for creative work: in primary school, I became interested in music and composing music with sequencer and tracker programs. This was kind of programming music, and I think creative work is basically problem solving.
My studies at Tampere University of Technology in signal processing, statistics and machine learning helped me understand the connection between data, programming and mathematics in greater depth. I got a job at the Department of Signal Processing during my studies and ended up doing a dissertation in computational biology. However, the academic world did not feel like my thing, so I decided to enter the world of business after graduation. I applied for a job at a Swedish music start-up, where I started as a Data Engineer. It was great to bring together two things important to me: music and data.
Music and data together – that sounds cool! And how did Nitor enter the picture?
A couple of years went by quickly in Sweden, where I learned a lot from my colleagues. I felt that the project in question had run its course for me. The idea of returning to Finland was also attractive. I saw a job advertisement from Nitor on LinkedIn. Nitor seemed like an interesting company, and its Great Place to Work awards attracted my attention. I started working at Nitor in spring 2019.
What does the working day of a Data Scientist at Nitor involve?
As a Senior Data Scientist, I use data extensively to create added value for customers. The tools required include statistical modelling methods and prediction of business trends. With them, I can help customers make better business decisions with data.
Data processing automation and the development and maintenance of the models and software produced are also an integral part of the role of the Data Scientist. Therefore, it helps a lot to know the basics of software production and what it means to be part of a software team.
Important technologies used in daily work include different data warehouses, computing environments and data processing tools. Amazon Web Services plays a big role, and Python and SQL are the most widely used programming languages.
Eero at Nitor's Spa Lounge
What is the best thing about this role? What motivates you the most?
Problems solving, definitely, and the fact that your work genuinely helps customers. Customer feedback is always very motivating! Data modelling helps customers make better business decisions. In this job, you get to learn new things all the time.
What kind of a team is Nitor's analytics team?
We have a very qualified, relatively small and close-knit group. It's amazing that I can constantly learn from my teammates! Together, we review publications and technologies related to the field and other theoretical articles that support our work. A small group also provides the opportunity to influence the direction in which the company is developed.
I feel that Nitor's success in the Great Place to Work awards is deserved. The work culture is really good: Nitor provides strong support for work and encourages a good work-life balance. We have good benefits and the people here really want to develop Nitor's work culture.
The best thing about working as a consultant is that I can work on varying projects with different customers, get to see different environments and solutions, and work with different people and technologies. This is an excellent environment for learning!
You said that music is close to your heart. How does Nitor make it possible to balance work and free time?
At Nitor, employees' well-being is taken seriously and their work-life balance is a top priority. Of course, there are also many hobbyists and clubs among the Nitoreans; on my first day at the office, I was invited to join Nitor’s synthesiser club and we have since had jam sessions at the office!
Artificial intelligence, machine learning and data science are part of sustainable digital development, including pragmatic architecture, design, large-scale agility and technology services already in place at Nitor. In this blog series, you get to know the data wizards at Nitor in more detail and see how they solve our customers' problems in utilising data.