We are looking for a motivated Working Student Fraud Data Engineering / Analytics to support our Fraud Engineering team. You will work with fraud-related data, support fraud monitoring and investigation processes, and contribute to dashboards, reporting, and scalable fraud detection logic across modern e-commerce operations. This role combines Fraud Analytics, Data Engineering, SQL, Python, and Business Intelligence and offers hands-on experience in building data-driven fraud prevention solutions without impacting customer experience.

Your Responsibilities

• Support the Fraud Engineering team with data analysis, fraud monitoring, and fraud investigation across e-commerce processes

• Prepare, structure, and analyze large datasets using SQL, Python, and analytics tools

• Contribute to the development of fraud detection logic, dashboards, reporting solutions, and internal fraud analytics tools

• Help identify fraud patterns, suspicious behavior, account abuse, payment fraud, and operational anomalies through data-driven insights

• Collaborate closely with cross-functional teams to improve scalable fraud prevention processes and data quality standards
  

Your Profile

• Ongoing Master’s studies in Data Science, Data Engineering, Computer Science, Business Informatics, Statistics, Mathematics, or a comparable technical field

• Good practical knowledge of SQL and experience working with structured datasets and analytical workflows

• Basic experience with Python for scripting, automation, or data analysis

• Strong analytical mindset with interest in Fraud Detection, Risk Analytics, Payment Fraud, Account Abuse, and E-Commerce

• Structured and hands-on working style with the ability to work independently while collaborating closely with the team
  

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