Data Scientist (various levels) - Credit Risk

About Klarna
Klarna was founded in Stockholm, Sweden in 2005. Since then we've changed the banking industry forever. And now we're creating the world's smoothest shopping experience. We serve over 90 million consumers worldwide, and partner with 250,000 merchants – with a new merchant joining us every 8 minutes. Including some of the world's leading brands, such as H&M, ASOS, IKEA, Adidas, Samsung and Lufthansa. Our offices are spread over 17 different markets, hosted by 5000+ employees from 100+ nationalities.
As Data Scientists, we are seeded throughout Klarna’s businesses, either in small technical teams owning a problem space, or embedded as experts in cross-functional teams containing Product Managers, Engineers, Designers and more. We work hard to build Data Science products that our customers will love, and we take great pride in owning models end-to-end, from prototyping to production. You can check out some of our recent projects at engineering.klarna.com.


What you will do:
Empower Klarna’s risk managers with highly accurate risk scores for consumers, merchants and transactions.
Take an instrumental role in product development, to ensure the continued success of Klarna’s Pay Later, Financing, and Card products in numerous global markets.
Further enhance your skills in practical Machine Learning and Software Engineering, by developing state-of-the-art predictive models, creating end-to-end data pipelines and deploying your systems in Klarna’s cloud environments.
Collaborate with extraordinary people from all over the world, each with their own perspective, background, and expertise.

The right person for this role has:
Experience related to risk, portfolio management, banking, finance, model validation, or product analytics.
Experience developing classification models with machine learning techniques.
Experience working with Python, SQL and Git, and an understanding of the concepts behind cloud computing technologies.
A deep understanding of the theoretical foundations behind classical and recent machine learning models and algorithms, such as generalized linear models, random forests, ensemble methods, and deep neural networks.
Great communication, organization, and team working skills.
A university degree in a highly technical, numerate subject (e.g. Mathematics, Physics, Engineering, or Economics).



How to apply:
Send over a CV in English.
Does it sound exciting for you? Then apply to be a part of a challenging journey together with the rest of the movers and shakers of our future society.
We'll be reviewing applications on an ongoing basis. Candidates from all over the world who meet the requirements are welcome to apply!
Klarna is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates. Please refrain from including your picture and age with your application.