Job hinzufügen
Klarna

Data Scientist - Credit Risk

Stockholm, Sweden
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 200,000 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 3500+ employees from 90 nationalities.

Data Science plays a vital role in Klarna’s operation. Historically, our focus areas have revolved around real-time risk decision-making for transactions. This can either pertain to credit assessment for individuals or identification of fraudulent transactions. Since then we have added many new data science areas such as predicting customer lifetime value, predicting return behavior in e-commerce, etc. 

As a Data Scientist at Klarna you will:

  • Develop state of the art models to classify transactions and individuals
  • Bring your ideas to production using AWS
  • Be involved in the whole process of model development. This includes everything from root cause analysis, data collection and feature engineering to training, validating and implementing machine learning models, computing performance statistics and live model monitoring
  • Work closely with several engineering teams and business analysts to find new and smart ways of consolidating data and making use of it in order to make better models and ultimately better predictions
  • Be part of the Engineering organisation. Hence your workflow will be software-driven in terms of deploying models to production, using version control, and in general employing software engineering best practices
  • Be innovative, cooperative, collaborative, open and have a flexible mindset with critical thinking

In order to be successful in this role we believe that you will have:

  • Strong programming skills in Python, SQL and experience with popular machine/deep learning packages
 (e.g. scikit-learn, keras, tensorflow, mxnet)
  • Experience with & knowledge of:
  • Cloud platforms such as AWS or Google Cloud;
  • Big data using Hive, Spark, EMR
  • The theoretical foundations of classical and recent machine learning models and algorithms, such as generalized linear models, random forests and ensemble methods, deep neural networks etc.
  • A degree from a university in a highly technically numerate subject (e.g. Maths, Physics, Engineering or Economics).
Do you recognise yourself in the description? Apply by following the steps below and attach a CV/resumé in English. We look forward to your application!

Interesse geweckt?

Jetzt bewerben

Weitere Jobs