Marko Apostoloski is an ML Engineer at Data Masters and a perfect example of how one can make a successful career switch. Three years ago he decided to go in another direction and start a career as a Data Scientist, although he is a mechanical engineer by education and worked in that field for four years before joining Data Masters.
Our People & Culture
We sat down with him to reminisce on his beginnings and how his career progressed through the years. This is his Data Masters’ story.
The beginnings in Data Masters
First I would like to note that I am a mechanical engineer by education, and I have worked in the automobile industry before coming to Data Masters. You can say that at first, I was working in the domain I had chosen, but I needed a change. That change came when I enrolled in a Python course and then I was initially recommended for an internship at Data Masters. In the beginning, I wasn’t keen on becoming a Data Scientist, but that quickly changed, and I am happy because of that. I started by working on a discrete event simulation project for an American client, the next project was building a demand forecasting model for a pharmaceutical company.
In all that I was guided by my mentor, Martina Naumovska, from whom I have learned so much about data management and business domain knowledge. I would like to mention that in the past year, Martin Vasilkovski has had a big influence on my knowledge, and consider him a great mentor.
First impressions of the company
My first impression was the friendly atmosphere and the full-on support between colleagues, which to this day remained Data Master’s hallmark. We were 15 employees when I came to Data Masters, and now we are around 50, so I got to see the natural progression and growth, but the company’s spirit remained the same. That’s the people’s side of it.
From a business perspective, in the beginning, we were focused on on-premises solutions because the client’s needs were dictating that approach, but lately, we are focused on working on a cloud, because it offers scalable solutions, or in other words, you can upscale or downscale your resources according to your current needs.
Educational background and work experience
As I have mentioned my educational background is in mechanical engineering and I worked as a mechanical engineer in the automobile industry for four years, before making a career switch to Data Science. One of the hallmarks of my education journey is the Data Science Academy that I visited in 2020 which had a major influence on me. After that, I was also a lecturer at the Data Masters Academy where I taught Time Series.
In the near future, I want to upgrade my knowledge and focus on Data Engineering on a cloud. The company supports my growth by giving me time and covering the costs for the certification, which I consider an amazing perk of working here.
Data Masters’ approach to working with clients
Almost every client that we have worked with so far has the same pain point – they spend too much time analyzing the process cycle and they have untimely reports. We help them by elevating their solutions (which are mostly on-premises) so that as a result they can get timely reports to make efficient and ad-hoc decisions. Some of the solutions require the optimization of existing on-premises solutions or the development of additional solutions, but when we are dealing with large sets of data our recommendation is to migrate to a cloud. The benefit of this type of migration can be seen immediately, mostly by getting timely reports, but also by setting a baseline for building solutions for future purposes.
One of the most important benefits of our approach is that we are not just building solutions, but also we train the employees on how to use them. There is a time period after the development of the solution, where we take care of the maintenance, but after a while, the employees can take over the process with minimal involvement on our part.
Projects and technologies
I’ve mentioned briefly that my first bigger project was for a pharmaceutical company where we were focused on building a demand forecasting model. Most of the time on the project was spent on data processing and product segmentation, because of the numerous product demands we had to predict. Personally, the biggest project I have been involved in so far is a project in the HR domain, where we worked on text classification, and used advanced NLP models supported by neural networks.
On Data Masters expansion in Portugal
Our expansion in Portugal has two major advantages: the company can bring new projects with various complexity, and the employees will have the opportunity to expand their knowledge by working with major league clients. It’s important to note that Lisbon is compared to Silicon Valley, so having that in mind Portugal is a very smart move so that we can show our knowledge to the world market.
Data Masters' strongest suits
I can answer this by taking into account two things: seeing it from a business perspective, one of our strongest suits is that we are developing tailor-made solutions and we have a very open mind to the client’s challenges. This is crucial because, in the first phase, the thorough analysis of their needs is the basis on which we build the solution. And we never use the same solution twice.
The second perspective is seeing things in how we work and share knowledge. We have an agile approach to working and knowledge sharing, additionally to that the Academy helps in building the next generation of Data Scientists, and we use every opportunity to exchange our experience of working on projects in different domains so that we can have a more objective approach when a similar project comes to us. Also, it contributes to having a transparent approach to our work.
Teamwork dynamics
We use a very solid principle to approach the work: the tasks are distributed equally, but when there are major challenges, everyone chips in. There is a hierarchy in accountability, which comes with the level of seniority of the members, but when it comes to cooperation, there is no separation, nor do we accent seniority. We are team players and always available for each other.
Mentorship process
One of the biggest perks of the mentorship process at Data Masters is that every junior member is given a significant amount of trust in completing his tasks. This contributes to developing accountability toward work and tasks because accountability comes with the job itself. We are not fans of micromanagement, but we cross-check the tasks so that we can see the progress of the employee.
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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