What Does a Data Scientist Do?

Daniel Völker, Lead Consultant Data Science & Conversational AI
Diana Krüger
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Our colleague Daniel Völker from Berlin tells us something about his role as Lead Consultant Data Science & Conversational AI at valantic and how he wants to develop in this area.

Please introduce yourself.

My name is Daniel Völker, I am 34 years old and I have been with valantic for 5 years in the fields of Data Warehousing, Business Intelligence, Data Science, and Artificial Intelligence. I am currently a contact and team leader for the Data Science and Conversational AI divisions.

How did you originally come to valantic?

I had a student job at IBM, and I studied the AI (Watson) portfolio there intensively. From there, the path to valantic, as IBM’s Gold Business Partner, was not a long one.

What do you do in your role as Data Scientist and what does your day-to-day work at valantic look like?

My day always starts with a coffee: Either at home, in the office, or at the customer’s. Since I live in Berlin and my office is in Hamburg, I am (currently) in the home office a lot. But I still manage to go to Hamburg now and then. As team leader and project manager, a large part of my day-to-day work consists of meetings, workshops, and project planning. In addition, I spend a lot of time with my team enhancing applications in the areas of data warehousing, business intelligence, data science, and conversational AI. Together with our marketing team, I also create content for data science and AI campaigns and present webinars on these topics.

Data science and conversational AI are trend topics of the future: What do you like about these topics?

We have been trying to automate things since the beginning of the “digital revolution.” Data science and conversational AI are two essential building blocks on this journey. Using data science, I have the opportunity to make predictions and recognize patterns in my data that were not yet clear to me with business intelligence. Conversational AI can design human interaction and automate simple tasks. I therefore find both topics extremely multi-layered and exciting. There are a lot of points of contact with a wide variety of disciplines, which ensures that you learn a lot. Through the exchange with the technical departments, I see every day how much potential there is in these topics.

In three to five years, we will have reached the data science and conversational AI productivity plateau. It goes without saying that business experts must extend their business intelligence reports and plans to include data science reports. For many end users, it will be normal to contact a chat- or voicebot that can automatically answer various requests or even take care of them immediately.

What do you particularly like about valantic in addition to the wide range of different topics?

The open, fair, and human interaction. The most important element in a digital world is the people. At valantic it is very important to us to interact well with both colleagues and business partners. Direct communication and fairness characterize our behavior.

And where do you see yourself in three years?

My goal is to develop myself professionally and personally. I can only do this if I am confronted constantly with different challenges and continue to develop. As a team leader, I would also like to be seen as a role model. That’s why I will take on more management and human resources responsibilities over the next few years and expand my skills in these areas.

Thank you, Daniel, for the great conversation!

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