Data scientist is the most sought-after profession of the future in many industries. Everyone wants someone on their side who understands the data that is being collected in enormous quantities in modern circumstances. Insights from data can be used to make strategic decisions about business development, as well as everyday moves that mean profit. Since data scientists are few in Croatia and at Lider’s editorial office we love having a concrete example, to gain a quality insight into what data scientists actually do, we set out to search for real-life examples. Here’s what we learned from Andrea Pirša Ilić, head of cognitive computing at A1 Croatia.
She started working with data while studying at FER, working in the Business Intelligence department at A1, where she participated in a machine learning project for her thesis.
– Along with the data analysis I was engaged in for most of my working hours, I always aimed to implement some new solutions and programming. The implementation of the first real project in the field of machine learning was a combination of programming, algorithms, and analytics, that is, the ideal combination of skills I wanted to develop – says Pirša Ilić, now head of cognitive computing at A1 Croatia, where she develops solutions based on artificial intelligence.
More specifically, in addition to developing solutions with clients and coordinating the team, she analyzes and prepares data daily, develops machine learning models, and implements applications that use AI solutions.
– In the work I do, there is no daily routine; how the day will look depends on the projects we are working on and what stages of development they are in. A large part of my working hours involves following research in the field of artificial intelligence and currently available technologies and their application to specific projects – says Pirša Ilić, commenting that the most common misconception she encounters is that anyone can become a data scientist ‘overnight’. She notes that she is pleased when people from her surroundings find some applications of data science in their domains, for example, how predictive models could be used in medicine.
