Senior Data Analyst (Fraud)

Google Chrome Microsoft Edge Apple Safari Mozilla Firefox Senior Data Analyst (Fraud)Full-timeCompany Descriptionfoodpanda 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 DescriptionAs a Senior Data Analyst, you will leverage your expertise to directly impact the growth of our 16 markets by delivering actionable insights and advanced analytics solutions. In this role, you’ll work closely with senior stakeholders, mentor junior analysts, and shape the analytics function within one of our functional analytics teams. This is a high-visibility position that plays a pivotal role in data-driven decision-making.Own a risk & fraud problem domain end-to-end, framing ambiguous problems and delivering analytical solutions that drive measurable improvements in cost, efficiency, service performance and customer experience.Act as a thought partner to business and domain leads, shaping problem statements, challenging assumptions, and co-developing data-driven solutions to high-impact risk and fraud challenges.Apply advanced analytical methods, including simulation, optimisation, and statistical modelling, to detect and solve complex problems such as incentive abuse, refund claim abuse and.Determine causal impact in operational environments, designing and analyzing experiments (e.g., cluster, switchback) and applying causal inference methods (e.g., DiD, synthetic controls) to inform business decisions.Build and scale data products and analytical tools, leveraging modern data stacks and agentic AI workflows to enable deep dives, self-serve analytics, and faster decision-making.Drive exploratory and root cause analyses, identifying performance drivers and uncovering opportunities for optimization across the risk and fraud infrastructure.Collaborate cross-functionally with data and engineering teams, contributing to data modeling, metric definitions, and scalable solutions that accelerate time-to-insight.Communicate with clarity and influence, translating complex analyses into actionable recommendations and driving alignment across technical and business stakeholders. Find out more about our Data Analytics folks here: Turn insights into impact!Looking for a career in data analytics? This could be the opportunity for you!QualificationsBachelor’s degree in a quantitative field (e.g., Statistics, Operations Research, Mathematics, Computer Science, Engineering) or equivalent practical experience, with 5–8 years of experience in analytics or data science.Proven experience in risk & fraud detection and mitigation or operations analytics, with a track record of detecting and solving risk and fraud problems such as account sharing, detecting patterns and had delivered measurable business impact.Strong technical proficiency in SQL and Python, with experience working with large-scale datasets (e.g., writing efficient queries, optimizing performance, working with NoSQL or distributed data systems).Experience working with modern data platforms, preferably within the Google Cloud ecosystem (e.g., BigQuery, Vertex AI, Google Colab, Google Sheets), or similar cloud-based data stacks.Experience applying advanced analytical methods, including simulation, optimization, statistical modeling and outlier detection to real-world business problems.Experience in causal inference and experimentation, including designing and analyzing experiments (e.g., A/B, cluster, switchback) and applying quasi-experimental methods (e.g., DiD, synthetic controls).Strong problem-solving and problem structuring skills, with the ability to independently navigate ambiguity and translate business questions into robust analytical approaches.Additional...