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Junior Fraud & Payments Data Analyst

Delivery Hero — Germany · Posted ~2 hours ago

Junior Full-time Visa History ✓

Skills

SQL Python Fraud analysis Risk analysis A/B testing Data analytics Machine learning fundamentals Fraud prevention Looker BigQuery Machine learning

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Summary ✨ AI‑Generated

Join a data-driven fraud prevention team as a Junior Analyst. You will use SQL, Python, analytics platforms, experimentation, and machine learning workflows to identify emerging fraud patterns, evaluate controls, monitor risk metrics, and help improve payment security and profitability.

Highlights

Early-career analytics role focused on fraud prevention and payments, offering hands-on exposure to machine learning, experimentation, risk analysis, and cross-functional collaboration with product and engineering teams.

Description

Job DescriptionJob Ref ID: JR0084509 Be a part of a team where you will: Identify opportunities to reduce fraud losses on different streams and improve overall profitability by leveraging advanced risk rules and Machine Learning. Implement end-to-end fraud prevention strategies—design controls, execute rollouts, measure impact, and iterate for continuous improvement. Support the evaluation of fraud prevention controls by assisting in the setup, monitoring, and performance analysis of A/B tests. Collaborate with stakeholders like Product, Engineering, Data Science to propose innovative and preventive fraud controls. Perform risk analysis using SQL, Python and analytics platforms (e.g. Looker, BigQuery) to identify emerging fraud patterns and monitor key metrics. Contribute to machine learning workflows by partnering with Data Science: define relevant features, validate model outputs, and flag performance drift. Maintain and optimize a centralized escalation process for suspected fraud, ensuring timely reviews, feedback loops, and alignment with local teams to adapt risk controls regionally. Develop and maintain executive dashboards in Looker to track fraud OKRs, financial exposure, and compliance metrics. Drive clarity and resolve ambiguity on complex fraud topics, using data-driven approaches, simplifying concepts for different audiences (local ops, senior leadership, or external partners).