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Junior Fraud Risk Analyst

Delivery Hero — Germany · Posted ~1 hour ago

Junior Visa History ✓

Skills

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

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Summary ✨ AI‑Generated

A junior fraud-risk analytics role focused on identifying emerging fraud patterns and improving prevention strategies. You will use SQL, Python, analytics platforms, A/B testing, and machine-learning workflows to design and evaluate controls, monitor key metrics, investigate risk patterns, and collaborate with product, engineering, and data teams.

Highlights

Junior analytical role combining fraud prevention, machine learning, experimentation, and cross-functional collaboration, with opportunities to work on measurable risk and profitability improvements.

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).