After a year full of learning, assignments, mentoring and completed projects, we have new student employment from the Data Science Bootcamp.
This employment is second in the line, with our partner company, i.ERP from Slovakia – a company that operates in the field of AI-powered Business Predictions.
Ivona Ristova showed high performance at the Bootcamp and was in the group of students recommended for employment to our partner i.ERP.
Ivona and Nikola were selected after the interviews, to join their team of Junior Data Scientists.
Find out how Ivona, in one year, from an engineer for planning and optimisation reached a career in Data Science, in a prestigious international company.
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Brainster: Ivona, first of all, congratulations on the excellent completed team project and the new job position in i.ERP. Let’s start from the beginning, where did the desire for Data Science come from?
Ivona: Thanks for the congratulations and of course for the interview. The idea of a Data Science career is attractive, but the way to get there can be difficult.
I consider myself as a person that constantly wants to learn. After graduating from the university, I started working with data and their processing and analysis. Of course, technological advances provide a more sophisticated way of processing and analyzing. So Data Science was a logical continuation of the story.
Brainster: What was the crucial moment for you to decide on a career change, from an engineer for planning and optimisation to a Data Scientist?
Ivona: As I mentioned, data analysis involves statistical methods implementation. So Data Science was an ideal complement to the experience I already had.
I was already interested in advanced data analysis methods and finding a way to add value to them. Data have become a treasure trove available to all companies, but not all use it. The goal is to use that data in the right way to get a business model that describes the data and benefits us.
Brainster: Data Science Bootcamp is the hardest one in Brainster that requires to “warm up the chair” and to dedicate one year only to learning. How much do you think the dedication helped you to get a job immediately after graduating from the Bootcamp?
Ivona: It is necessary to go through many crossings to climb a mountain. Of course, there is no science without trouble.
Despite some guidance I have had before, these results I have achieved with full commitment. Realistically, this is the beginning of my story, as the foundations are laid down now. The next step is to work on the remaining parts.
The Bootcamp is the first step in entering this science. To learn how it works and what the essence is. But reaching the goal depends on how much the individual is willing to commit and sacrifice in the process. There is much to discuss on this subject, but of course, commitment and perseverance are worthwhile.
Brainster: Working on a real project is a key point of the Bootcamp. How ready do you feel to respond to new challenges as a Data Scientist in i.ERP with the experience, you have already from working on a real project?
Ivona: The real project is the most important part of the program. With this, the students practically enter the data world. Here you can apply and implement all the previously mastered methodologies and knowledge. This is where teamwork comes into play – the division of responsibilities, to achieve the outlined goal.
i.ERP is a company in which with hard work and perseverance you can succeed and achieve results. I am grateful that I have someone in the team to learn from and to upgrade what I have as a basis. That is the most important thing for progress in the field.
Brainster: As an engineer for planning and optimisation, you have worked with VBA. But at the Bootcamp, you learn a much more advanced toolkit based on Python, that you master with high performance. What are the ideal predispositions to be good at programming or working with data? Advanced Excel?
Ivona: The basis of data processing and analysis is what we want to emphasise from the data. The way of interpreting the results is different. With Python, we can emphasise the values of the data much more. There are libraries in Python that are very advanced and with them, the analysis is quickly done, unlike in Excel that is too large or even impossible for analysis.
If I have to summarise, it is important to know the area of data analyzing and with that, we already have an advantage. But, also, if we have a mathematical background, we have a parameter with which we can work more firmly. It’s the statistics that guide us through the data. The tools are the ones that only allow us to translate all those analyzes to be adaptable for reuse. That is why I would say that mathematics and statistics are the most important predispositions for anyone interested in working with data.
Brainster: What is necessary to successfully overcome the challenges that came from the Machine Learning module?
Ivona: Lots of learning, perseverance and endurance. IERP
Brainster: And finally, what would you recommend to anyone considering learning Data Science and to our active students who are in different stages of the program?
Ivona: Let the data tell you a story that you can turn into a picture. The art of data is a tough challenge. I can confirm that with 95% accuracy.
If you have ever thought about a future-proof career in Data Science, have a look at our remote Bootcamps.