Our People & Culture

Many experienced professionals have been in this situation, wanting to switch careers even after they’ve had several years of experience. For Nikola Arsovski, an Economics graduate, the desire arose when he realized that the data he worked with had much more potential than what it was being used for. And thus, his career transformation journey began right here, at the Data Masters Academy. 

In this edition of Our People & Culture, Nikola shares his unique perspective on what it was like to go from working in the banking sector to becoming a Data Analyst and how Data Masters have helped him in his journey.

Entering the Data World Through the Data Masters Academy

I enrolled at the Data Masters Academy because I wanted to improve my skills in data analysis, visualization, and statistical modeling. At that moment, forecasting models were a hot topic that piqued many people’s interest, including mine. Due to my knowledge and expertise in the financial and banking sector, I had a sound basis for “entering” the data world. Additionally, I would like to note that, although a large portion of the material that we covered was unknown to me, especially the technical aspects, the Academy was perfectly tailored for students like me. After I had finished the Academy (quite successfully, in my opinion, 😀), my career at Data Masters began.

The necessity to improve and upgrade my technical and engineering skills was clear to me after my very first project experience. Upon taking steps in this industry, most people wish to work exclusively with Machine Learning, data analysis, and visualization. However, as some of my colleagues have already mentioned, the current needs of the companies are not quite on that level yet. Namely, banks and financial institutions in the region and organizations in other industries have a more pressing issue – better and more functional data organization. 

This is where the need for me to further familiarize myself with the functionalities of numerous applications, tools, and concepts arose. 

Becoming Part of the Data Masters Team

Even before I was employed at Data Masters, I generally knew the people in the company on a personal level, and I liked the team itself. While attending the Academy, I was further convinced that they are a group of hard-working, dedicated professionals who love what they do.

I’m currently part of the banking division at Data Masters. I can say that we are an unconventional mix of tech-savvy individuals and people who possess business knowledge. I believe that the distinctive way we function and complement each other and the teamwork that we have built are some of the main traits that allow us to efficiently help one another, creating a unique entity that works extremely well.

Those of us who have greater business knowledge try to improve and upgrade our technical skills so that we can become more independent in that aspect. Meanwhile, the rest of the team members who have a technical background gain insights from us about the logic and context of the data. 

I can also say, quite confidently, that we are a well-oiled machine, not just the members of my team but all the others outside of it as well. Moreover, I would like to point out that one of the main characteristics of Data Masters is the cooperation and support that exists between all employees.

Recognizing the Need for Better Data Organization in the Banking Sector

During my time in the banking sector, I realized that there is a need for better data organization. What I mean by this is that banks and all other companies use various reports daily. To do this, they either generate the reports from their system directly or have access to a particular database that they use to create manual reports. Here, they generally face two adverse situations:

First, the business needs to obtain information relatively quickly to make a decision. However, the report generation process takes a lot of time, mainly due to the volume of data and the way companies store their data. 

Second, in cases where different departments need to access the same information, they get different results because they obtain the data in different ways. Namely, the companies do not have a single source of truth in their reports. As a result, it falls upon the analysts to correct any mistakes, compare different reports, and check the accuracy of the data, preventing them from using that time for doing analysis and drawing conclusions.

Although I was aware of the need for data organization, i.e., data governance, I did not know the scale of this problem and what challenges arose to solve it while I was still working in a bank.

The Current Data Landscape in Macedonia

Despite being a small country with a relatively small market, companies are slowly but surely starting to recognize the benefits of what we do. The lack of proper data organization, unified reports (a single source of the truth), and employee access to clear and accurate information, alongside the extensive dependence on in-house IT sectors, cost companies a lot of money and time.

Although the changes are currently developing at a slower pace, companies across all sectors are actively working on optimizing and organizing their data, both to meet regulatory requirements and improve their daily processes.

Even though we can identify a trend among companies in improving their capabilities in this domain, we are still far from what is currently most prominent worldwide, which is machine learning and AI.

I believe that the digital transformation that domestic and regional companies are currently undergoing is a path that must be taken. We can’t jump from using unorganized Excel files to ChatGPT overnight. Even the most advanced AI models require clean and accurate data to give precise results. Hence, the well-known metaphor in the data sphere emphasizes what I previously mentioned: “Garbage in—garbage out.”

So, even though the journey is filled with challenges right now, this is an essential transformation process that must be done, and Data Masters as a company is here to walk the path with companies. 

Where Will the Future Take Us?

I think that banks will start implementing ML in their operations. Moreover, I believe that banks will undergo both a technical and business transformation. Banks have thus far avoided a technical transformation because it was not essential for them. Their business model brought them satisfactory returns without the use of advanced technologies. However, due to increased competition, the difference between those who chose to walk the path of technical and technological development and those who continue to work with outdated tools will soon become apparent.

We, as Data Masters, can improve their processes and guide them, hand-in-hand, on the road to more advanced technologies.

Over time, as advanced AI and ML solutions start to be implemented in the banking sector (both in Macedonia and the region), the work of bankers will experience a transformation, turning into a role that is more focused on consulting rather than administrative tasks. In the future, bankers will serve more as advisors to clients.

By understanding their system’s background models, the main tasks of bankers would be to offer the best solutions to their clients and advise them on what characteristics they should improve and which product they should choose. This will enable them to provide the most optimal service and products that will best suit their client’s needs. In fact, by understanding the ML models used for credit scoring, bankers will be able to advise clients on how to change their features, optimizing them according to their importance in the ML model itself.

Personal Goals & What’s Next

The general direction of my career is towards fully understanding the business and learning how things work so that, as a data consultant, I can provide complete solutions, understand issues, and lead projects on my own, regardless of whether it would be in the engineering, analytics, or data science sphere. 

In the short term, my priority is to upgrade my technical skills and familiarize myself with data engineering and data analytics concepts. This includes learning about data organization, self-service data models, etc., which make up the foundation of our work. 

 I think that projects like building a data warehouse, data mart, and similar data solutions are quite valuable and may even be essential for me and for people who want to specialize further in data science, AI, and other such fields.

Aside from the engineering aspect, I recently had the opportunity to improve myself in data analysis and analysis of data solutions, mainly through projects in the banking sector.

Nikola’s Advice

My advice for future bankers, people from insurance companies, accounting firms, financial institutions, or any business-savvy individuals is that their domain knowledge is an excellent first step in the data world. However, they have to master the technical tools as well because, without them, they would be at a great disadvantage. So, anyone who wants to enter this field must make an effort to learn the technical tools thoroughly and, maybe even more importantly, the concepts related to data organization and data analysis, as these are the key ones that will ease their way into the industry.

The knowledge-sharing mindset between the employees is one of the most important components in the Data Masters growth and success in the past four years.

If you want to work on world-class projects with experienced professionals and you are not afraid to make mistakes (we learn and grow together), you are the perfect fit for us.

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