Interview - Sergi Sergiev


Sergi Sergiev is the Head of the Data Science Society and  founder of ShopUp, an IT Services company that specializes in IoT customer analytics in the retail sector.

Can you give us a little background on your interest and your background in Data Science?

I began working in the field eighteen years ago when graduating with a degree in computer science. I originally went to work for a consulting group where I participated in twenty-two projects in the finance and telecom sectors. Although at this time machine learning was mostly about decision trees, my interest grew for how data-driven decision making could improve business practice. I went on to do my MBA at the University of Vienna with an emphasis on Big Data in Manufacturing.

What is the context and the objectives of your current work of the Data Science Society?

I am intimately convinced that data, methodology, and technology can improve how we read, and ultimately how we understand the world around us. Whether it be with the students in the Data Science Society or with my customers in ShopUp, I feel Data Science can make a real impact and influence our chances of success in the foreseeable future.

The Data Science Society regroups this vision, a set of values and projects on a collaborative platform to support the community in this fast-paced and rapidly changing field. The challenge here is to set up a self-sustaining framework and to continually grow our membership. 

This ideal vision is of course challenged by the context and realities of Central and Eastern Europe – companies are more conservative than in the States and wary of new ideas and practices. Since the Data Science Society depends upon innovation and goodwill– if we can succeed here, we will succeed anywhere.

One recent project with the Data Science Society comes to mind. We ran a data hackathon earlier this year on identifying propaganda in the written press. The challenge here isn’t just “fake news”, but the dangers of how the presentation of the “facts” influences people’s opinions and mindsets.  We had three hundred registrations for the event and in the end, one hundred and fifty people from all over the world participated, and several of the models we produced demonstrate a 90 % accuracy rate. 


What opportunities do you see for Data Science in your field and market? 

In the retail market, ninety percent of all purchases are still done in physical stores. Online stores, together with IoT, will go a long way in helping both suppliers and their customers increase their visibility and their understanding of how goods and services are produced, marketed and consumed. Online and physical outlets do not form two separate markets but are extensions of each other – the better one sees the whole picture, the better the value for all involved.

Big Data isn’t just an opportunity for large corporations, it can be a game changer for the common citizen/consumer. It has often been said that social media companies know us better than our own mothers. If we accept this premise, the real challenge becomes how the data is used and stored. GDPR is just one consequence of this, for in the end there is a tradeoff between the quality of service and the availability of personal data. Some element of public regulation is certainly needed, but in the end, I can accept to loan my data to organizations in exchange for services that meet my needs and objectives. 

What specific advice can give students interested in developing their data science skills today?

I believe that the best classroom is the real world. Data Science isn’t an easy career, students need to follow their passions, look for sources of motivation, and be committed to life-long learning. I have learned by example, through experiments and experiences – it’s the best advice I can offer anyone looking to specialize in the field.

Look at the data that reveals real-life challenges and opportunities, as we do ourselves in our international Datathons. Continually explore what approaches can be used to model these problems and what methods can be leveraged to look for solutions.  The best reading isn’t in any book but in the interactions of the people and organizations around us.




In this issue :

Find that Panda

Seeing the Random Forest...

Let's explore how Random Forest is used in machine learning, as well as its basic assumptions and use scenarios


The BAI Spring Session

BAI Community News

In brief, the recent projects, conferences, bootcamps and publicatons of the BAI Data Science Community

The Business Analytics Institute

The  Practice of Data Science

In challenging the participants to think out of the box, the pedagogical program of tthe BAI Summer School will focus on workshops and case studies drawn from Health Analytics, Smart Cities, and Logistics.

 The Ambassador Program

Analytics in Action

BAI faculty facilitated a key module again this year in SDMIMD’s Analytics Track, Analytics in Action, in Mysore, India. 

The Paradox of Trust

Partner Interview - Sergi Sergiev

Sergi Sergiev is the Head of the Data Science Society and  founder of ShopUp, an IT Services company that specializes in IoT customer analytics in the retail sector.


 Airport Excellence

Trust by Design

The motor of the next industrial revolution won't be data, but trust...


This Newsletter has been created specifically for the BAI community to foster conversation around the use of analytics in improving business decision-making. 

Interested in our February Newsletter? It can be found here