From Algorithms to Insights: A Day with Addepto Data Scientist. Meet Vova

Welcome to our first Employer Branding Interview Series, showcasing the talented individuals driving our company’s success. Today, we’re introducing Vova, one of our Data Scientists.

In this Q&A, Vova shares their Data Science journey, daily work life, and insights on recent AI advancements. His experience with innovative projects in 3D object classification, object detection, and ChatGPT applications highlights the cutting-edge work at our company. Whether you’re a seasoned professional, a student, or simply curious about Data Science, this interview offers valuable insights into the field and our workplace. Join us as we explore Data Science through the eyes of one of our dedicated team members.

Career Inspirations

Addepto: What inspired you to pursue a career in Data Science, and what do you find most rewarding about this field?

Volodymyr Kepsha, Senior Data Scientist: I was studying computer science in my second year, I still didn’t have an idea of what I wanted to do in IT. During that year, we had a course on machine learning, and I fell in love with the idea of teaching a computer to perform complex tasks by itself. The past few years have been extremely intensive in terms of AI developments, and this indeed inspires me to work in this field.

Typical Day of Data Scientist

Can you describe a typical day in your life as a Data Scientist?

A typical day starts with preparation for a daily review, where I look over what has been done the previous day and outline my plans for the current day. Then, of course, there is a daily meeting where we discuss the status of our work. After the daily, I focus on my tasks. To stay focused, it’s important to take short breaks every hour (I use the Pomodoro technique for this). In the middle of the day, I have lunch and then continue with my work. When I work from the office, I enjoy playing ping-pong.

Techniques & tools

What techniques and tools do you rely on in your daily work?

My workflow strongly depends on the project I’m working on. For time management, I use the Pomodoro technique and other tracking services. Regarding tools, I use PyCharm, Visual Studio Code, Jupyter Notebook, and Docker.

Exciting Trends in Data Science

What recent advancements or trends in Data Science excite you the most?

I guess ChatGPT is one of the most valuable inventions in IT in the last decade. I was a little bit skeptical about GPT-2, but I was blown away by ChatGPT-3 and the breadth of knowledge it possesses.

Notable Projects and Outcomes

Can you walk us through some of the most interesting data science projects you’ve been involved in and their outcomes?

I have had a lot of exciting R&D projects related to 3D object classification, object detection and tracking for statistics gathering and resource allocation, object re-identification, and chatbots based on RAG. Many of the projects were proofs of concept, but as far as I know, a Face-ReID project I worked on progressed further to a minimum viable product.

How does working as a Data Scientist at our company differ from your previous roles, and what unique opportunities does it offer?

Working in this company offers me many more opportunities and challenging problems to solve. I also feel strong support from the company and feel valuable here.

How do you keep up with the rapidly evolving field of Data Science?

A, in general, is evolving quite fast. I’m subscribed to a few AI newsletters that send updates related to AI and IT in general, which helps me keep up with the numerous new developments. When I see interesting news about a new model, I read the paper to get more details. Also, from time to time, I check other resources that post state-of-the-art models.

Crucial Soft Skills for Success

What soft skills do you believe are crucial for success in Data Science, aside from technical expertise?

The ability to work in a team is essential, so communication is key. Additionally, I think a great data scientist should be able to explain complex solutions in simple terms, be well-organized, and have strategic thinking when leading a project.

What advice would you give to someone looking to start a career in Data Science?

Starting a career in Data Science requires determination, consistency, and resilience. Stay focused on your goals, continuously learn and practice, and embrace challenges as opportunities to grow. Remember, persistence and networking are key to building a successful career in this dynamic field.

Thank you!