Yuqing Li.

At Klarna, I feel that my work makes an impact.

Klarna Data Science Yuqing Li

Senior Data Scientist - I build data models that forecast Klarna’s growth and future purchase volume.

My path.

I’ve worked in the Forecasting team since joining Klarna in late 2019. I’d worked for Qliro and Sandvik as a data scientist and engineer but I was looking for a place where I could grow into a senior role. That came shortly after I finished my 6 months probation. I had been given the chance to redesign the processes we use for forecasting future volumes and growth in purchases. My hard work and ability shone through and I was made a Senior Data Scientist half a year into my time at Klarna.

Working at Klarna.

People at Klarna are highly motivated to deliver and I feel that my work makes a real impact. I like that a lot. There’s a lot of flexibility within the team on what tool to use, how to design your product, and how to design your process. There is a lot of freedom to make decisions, which is really fun. When you start there’s definitely a learning curve but once you get into it, things move impressively fast.

Something I’m unreasonably passionate about.

Detective novels. I like to find the bugs/loopholes in stories.

A day in my life.

AMPMEvening
Read emails about my job so that I am informed of any updates.Do some code review for my teammates and receive feedback.Read news about the financial situation around the world to keep up to date on any trends.
Drink water - very important to keep hydrated!Search cat gifs in slack (a lot of my colleagues are nice enough to share these).Have dinner.
Code to automate our process and also to make the process more robust.Enjoy some ice cream outside to make the most of the Swedish summer.Watch shows online to unwind before bed.

3 takes on Klarna.

My favorite Leadership Principle is...

Challenge the status quo because at Klarna we don’t believe in a single way to do something. We’re encouraged to try new things.

The best task of the day is ..

working on automating the forecasting process.

I’d describe my team as...

fast learners - we’re often working on improving our processes so we have to learn new tools and implement them from one week to the next.

Your success story starts here.