Aga Leyko loves a challenge. Her biggest driver is finding answers for her clients. 

Can you share the most interesting part of your career journey?

I have made two major transitions during my career journey. The first was leaving academia (studying the properties of elementary particles through a PhD program at the University of Bonn) for “a real job.” At first, I lacked confidence in my skills. Discovering that they’re translatable to business and applicable to real-world problems was amazing.

What’s exciting in this field is that we don’t really know where it’s going to be in five years.

The second transition was transferring from the Advisory practice in Switzerland to the Consulting practice in the United States, where I had to relearn how to do my job. Both transitions were extremely stressful, but absolutely worth it. Some say big changes like that slow down your career. For me, they provided new perspectives and an ability to see problems in multiple dimensions.

What excites you most about working with data and AI?

I’m still a scientist. My biggest driver is finding answers, and I love challenges. AI allows me to find data insights and present them to my clients in a quick and structured way. They can then use those insights to make data-driven decisions.

But what’s exciting in this field is that we don’t really know where it’s going to be in five years. We need to keep learning new skills all the time to stay up-to-date.

Describe an interesting project that you have worked on.

I really enjoyed working with health insurance claims data. Using clustering and classification models, I helped predict the outcome of claims and uncover patterns and root causes of claim outcomes.

AI allows me to find data insights and present them to my clients in a quick and structured way.

Working for health care gives me a lot of satisfaction. I feel that I’m giving back to the community after spending years in basic research. But claims data is also extremely challenging to work with. It’s available in huge volumes and is extremely sparse, so you have to be creative.