Our analytics team uses statistical methods and ML/AI modeling techniques to understand, and effectively break down hard problems. They love to crunch large volumes of complex data to derive meaningful and actionable insights. They identify good metrics, seek mathematical robustness and drive the development of solutions that deliver customer value. The team is composed of people with very diverse backgrounds, so today, we want to introduce Clara and Olga, both whom pursued a scientific career and gained a lot of experience in research during their PhDs and post-doc engagements before they joined KONUX.
Clara: I’m working as a Senior Data Scientist at KONUX for a bit more than 3 years now. I have studied mathematics with computer science as a minor. Originally, I planned to do a completely different minor, but the first compulsory computer science courses at the university really got me… This idea of using the computer not as a black box, but as a tool for automation and for solving complex problems was really fascinating for me. I decided to do a Master’s degree in statistics, a field that combines mathematics and computer science with data from the real world, and then continued with a PhD. During my PhD time, I was lucky to get the best of all three worlds: Developing a new statistical method with a solid theoretical foundation, applying it to real world data (in my case data from an Alzheimer study) and implementing it in an open-source software package to make it available to other researchers. It’s really fascinating for me to see where people found applications for my method, from medical data to ecology, ocean surface monitoring and even robotics.
Olga: Professionally I’ve been working as Senior Data Scientist in Konux (I joined just one month before Clara), recently also as team lead for part of the research team. What drives me? Trying to solve complex problems. As data scientists, we do that by combining different types of data to get understanding of the problem and generate useful insights for others.
Clara: For me, it all comes down to three things: 1) Exploring the unknown, seeing things that nobody else has seen this way before. 2) The moment when it all starts to make sense and 3) Turning data into information that can enable actual decision making.
Olga: Well, I think science is basically all about solving problems, whether it is in cosmology, medicine or, as we do, in engineering. The other great advantage of working in science is that you work with brilliant and inspiring people in an open and cooperative environment.
Clara: A problem where the solution is not immediately obvious, but where you can foresee that the problem in general is solvable.
Olga: I found my passion in infrastructure and engineering structures already at the university. I spent one year studying electrical engineering, but then switched to civil engineering because I got much more interested in these large and unique structures which are, often unnoticed, surrounding us in our daily lives. The civil engineering industry is more traditional and innovating slower than most others, exactly because each project is unique, influenced by uncertain environmental conditions and too large to be tested in a lab. But this is exactly what I found exciting and where I felt, with the use of modeling and data, one can have a big impact and find better ways to design and maintain the infrastructure.
Clara: Because it requires you to combine your knowledge with creativity. As a data scientist at KONUX, we’re almost always faced with problems or challenges that do not have an obvious solution. We work together in teams of people with many different backgrounds. The combination of all the experience in different fields and the open KONUX culture helps us find new and creative solutions for the railway industry.
Olga: It fits perfectly because at KONUX we aim to transform the way how the railway infrastructure and operations are done today. So it is a perfect place where I can make use of both my civil engineering and data science experience. And the whole team is built like that – we have people with very different backgrounds from engineers, physicists to statisticians and computer scientists. And when we combine all these perspectives and skills, we can come up with innovative and useful solutions for the industry.
Clara: Actually, to anyone, independent of their gender: Do what you love and not what others are telling you. In the end you will be the one doing it and not them.
Olga: I think to be happy and successful in science, you need what we call grit in KONUX. In science, the results of one’s work only come after a long time and the success is always uncertain. So you need a good deal of perseverance to overcome the obstacles and not give up on the way. And a second, equally important characteristic of a good scientist – in my opinion – is openness and honesty. You will make mistakes and you need to be ready to admit them to learn from them. You need to be honest about the assumptions you made in your research and limitations of your approach. You must enjoy being challenged by others and also challenge other peoples’ work. Because without these two ingredients I think you cannot do good science.