An expert in natural language processing, Anna joined Kumorion in summer 2023 as generative AI was sweeping the world. She explains how the company’s culture of trust gives her the freedom to do great work.
Please tell us how you were drawn to data science – specifically natural language processing.
I have always liked languages and mathematics. This field combines both, so it’s perfect for me.
When I went to Novosibirsk State University – in my home city in Russia – I did a bachelor’s degree in computational linguistics and a master’s in computer science. This was before generative AI became so widespread and accessible. At that time, large language models did not even exist and AI technologies were only just beginning to be adopted by industries.
After my studies I worked at a data-science consultancy focused on chatbot development, which is closely related to my expertise in natural language processing. Then in 2019 a startup specializing in speech recognition recruited me to Finland for a role here. After that I moved to a fairly large AI solutions and consulting company before joining Kumorion in the summer of 2023.
“My role at Kumorion has given me the chance to dive deeper into the technical aspects of data science.”
What was it about the opportunity at Kumorion that appealed to you?
I was not actively looking for a new job when a recruiter contacted me on Linkedin about the role here. But the timing was good, as I had reached a plateau in my previous role. I was doing a lot of research and AI model training.
My role at Kumorion has given me the chance to dive deeper into the technical aspects of data science. Here it’s more about developing workflow pipelines, as well as delivering and deploying solutions. It’s been a great opportunity to expand my skills and I’m very happy that I joined the company.
Please tell us more about the work of a data scientist and your tasks at Kumorion.
The role of a data scientist can be very broad – with responsibilities varying from company to company – but at the core you develop machine-learning models or statistics-based solutions. You also need to know how to aggregate, process and query data.
Developing models is not a major part of my role at Kumorion. I’m more focused on end-to-end data pipelines, looking at how we process data, apply machine learning models and output data to different interfaces.
I’ve also had to do some UI development, as I wanted my data visualizations to look good for when I present my findings to others in the company. I really like that there are many things I can try here.
“There’s a genuine culture of trust at Kumorion
– we are not micromanaged.”
How would you characterize working here versus working in a larger company?
I think the biggest difference is in the level of support and trust. It’s a small team, but I feel that I’m heard and my input is valued. This is something about Kumorion that I truly appreciate.
We get a lot of support directly from the leadership team. Our CEO and CTO are very approachable, so employees can really influence how things are done. There’s also a genuine culture of trust, where we are not micromanaged. I’m recognized as a professional who knows how to do the job.
So it’s the best of both worlds really: a culture of support and a culture of trust. This really motivates me to take ownership of my work and learn even more.
What do you think customers appreciate about working with Kumorion?
I think they value our flexibility; how we can quickly adapt and respond to changing customer requirements. We do not just follow a textbook approach – we take the time to understand what works best for the customer. In my opinion, Kumorion succeeds very well in this.
From other team members, I see a real dedication to delivering results. There’s a strong sense of shared ownership, where people are not just responsible for their individual tasks – they also take pride in our ability to deliver as a team.
“Exposure to so many different technologies has really helped me grow as a professional.”
What software tools and domains do you work with daily?
Python is the main language we use for programming in the AI team, but I work with a variety of other tools too. Recently I’ve been using Apache Airflow for orchestrating workflows, as well as MLflow for tracking the performance of machine learning models.
We work both with traditional SQL databases and data lakes. Thanks to the support of my colleagues, I’ve gained a much better understanding of the technical details across different cloud infrastructures.
This exposure to so many different technologies has really helped me grow as a professional. We work with a bit of everything here.
Is there part of your job that particularly excites you or is developing rapidly?
Lately I’ve been working on a project involving anomaly detection, which is something I’m really enjoying. We’re using machine learning models to analyze time series data and predict potential incidents in cloud services.
What’s exciting is how this project has sparked interest in other areas. After presenting our solution to a customer’s security team, they wanted to adapt it for their own processes too. I’ll soon be customizing it for those use cases.
It’s always rewarding to see your work expand and find new applications.