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Junior Fintech Analyst

Delivery Hero — Germany · Posted ~2 hours ago

Junior Visa History ✓

Skills

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

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Summary ✨ AI‑Generated

An entry-level analytics role focused on fraud prevention and financial risk. You will use SQL and Python to identify emerging patterns, evaluate controls through experimentation, monitor key metrics, and partner with data science teams on machine learning workflows and model performance.

Highlights

Work on high-impact fraud prevention and profitability initiatives using analytics, experimentation, and machine learning. The role offers hands-on exposure to risk strategy, A/B testing, data analysis, and collaboration with product, engineering, and data science 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).