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Description
About the role
You’ll be working in the Fraud and Payments team, which is responsible for processing 1% of all card transactions in Europe. This team is a cross functional team consisting of product managers, data analysts, software engineers and data scientists. Our engines inspect every order across all of our business lines to detect potential fraudulent behaviour and optimize the payment lifecycle – preventing financial losses due to fraud, optimizing payment costs and helping our users to successfully complete their payments.
Main tasks and responsibilities:
Working with a technical stack consisting of Python, Docker, SageMaker, Airflow and Databricks
Building and improving fraud prediction models using different predictive approaches
Exploring techniques that can improve the way we manage payments, including Causal and Reinforcement Learning
Handling the entire lifecycle from project conceptualization and notebook prototyping to productizing and maintaining a machine learning based solution or other automation that might be serving hundreds of millions of users in production
Leveraging our in-house data and model platform that allows you to launch new projects in a matter of days
Deploying and A/B testing solutions for millions of users, enabling fast feedback and measurable added value to customers
About you:
Exceptional knowledge of machine learning algorithms, statistical inference, and autonomous decision-making systems
Enthusiasm to collaborate with different roles in product, analytics and engineering to identify problems, explore trends and untap growth opportunities
Passion for continuous learning and a collaborative mindset, valuing open technical discussions and peer-to-peer knowledge sharing
Mastery in Python and SQL
Previous experience in fraud detection, payment optimization or related financial services is a plus
Strong academic background in a quantitative field
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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