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Delivery Hero · Barcelona, Spain
Glovo is part of the Delivery Hero Group, the world’s pioneering local delivery platform, our mission is to deliver an amazing experience—fast, easy, and to your door. We operate in around 65 countries worldwide. Headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. Job Ref ID:  JR0076157 YOUR MISSION Courier fraud costs Glovo millions a year. Account sharing, GPS spoofing, cancellation abuse, payment manipulation. Your job is to make that number smaller, end to end. You’ll design the detection logic, build the models, ship the dashboards, and push AI into the anti-fraud pipeline across every Glovo market. The problems are adversarial, the data is messy, and every percentage point you recover hits the P&L.   THE JOURNEY Own the global fraud strategy. Define rules, thresholds, and detection logic across all markets. Iterate as fraud patterns evolve. Partner with Operations and Legal to align enforcement with local regulation. Build detection frameworks that scale. Design and ship heuristic scores, rule engines, and anomaly flags for cancellation abuse, account sharing, GPS spoofing, and payment fraud. Work with Data Engineering to keep them running in production. Bring AI into the pipeline. Scope ML use cases, partner with Data Science to build them, and own the path from prototype to deployed model. If central doesn’t build it, you do. Ship dashboards local teams actually open. Build self-service monitoring so ops teams across 10+ markets can spot signals and act without waiting for you. Collaborate with local operations to make the tools fit their reality. Quantify impact and drive decisions. Run deep-dives that end in countermeasures, not slide decks. Give leadership clear, regular reporting on fraud trends, financial exposure, and what’s working. Think like a courier. Understand their incentives, pain points, and the vectors they’re exposed to, so the solutions you build are effective and fair. WHAT YOU WILL BRING TO THE RIDE Must have 3+ years in a data analyst or analytics engineer role, with a track record of turning analysis into business decisions Strong SQL and Python. Production-grade queries and scripts, not just ad-hoc notebooks Hands-on experience with AI/ML. You’ve scoped use cases, built or partnered on models, and taken them from prototype to production. You don’t just consume models, you push them forward Structured problem solving.