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Über
The Data Science (Consumer and Risk) team at Riverty is looking for skilled professionals to build Risk and Fraud machine learning models for our online payment products. Our primary goal is to determine who to accept and whom to decline based on data from past customers. This involves both detecting fraudulent transactions and identifying trustworthy ones by analyzing payment histories of similar customers.
What you are expected to do:- Participate in the entire modeling process, from data cleaning and feature engineering to model training and evaluation.
- Anticipate potential issues in the model-building process and suggest strategies to mitigate pitfalls.
- Engage in coding and code reviews to ensure quality and efficiency.
- Collaborate within a cross-functional team to drive innovation and effectiveness.
- A bachelor's, master's, or Ph.D. in a STEM field (e.g. Computer Science, Mathematics, Statistics, Engineering, or related disciplines).
- Experience working with transactional databases or case handling systems.
- Ability to work with unstructured data.
- Knowledge of SQL, relational databases, Spark, Databricks, VS Code, and Docker.
- Hands-on experience deploying models into production.
- Proficiency in Python for data science applications.
- Familiarity with common data science frameworks in Python.
- Experience writing production-ready Python code.
- A strong interest in learning new tools and technologies.
- Previous experience in the risk and fraud domain will be a big plus.
Sprachkenntnisse
- English
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