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Our client is looking to fill the role of Data Analyst. This client is a global commerce leader that empowers people around the world to buy, sell, and give. With a strong commitment to diversity and inclusion for over 20 years, Client offers an environment where you can be yourself, do your best work, and make a meaningful global impact. The Global Risk & Protections team plays a critical role in enabling safe and trusted commerce by deeply understanding payments and platform risk. We leverage advanced analytics, data-driven insights, and scalable solutions to deliver exceptional experiences for buyers and sellers worldwide. We are seeking a highly motivated, analytical, and collaborative professional who is passionate about using data to solve complex risk problems and shape the future of risk management at Client.
Job Responsibility:
Develop Risk Insights: Analyze large datasets related to incidents, near misses, and product or portfolio performance to uncover actionable insights that improve risk controls
Design and Implement Risk Policies: Support the creation and deployment of risk policy frameworks covering credit risk, fraud prevention, product and portfolio risks, access policies, limits, and funds availability
Monitor and Optimize Risk Strategies: Continuously assess the performance of existing risk strategies and identify opportunities to improve policies, operations, and outcomes
Cross-Functional Collaboration: Partner with global risk, product, and payments teams to deliver scalable, end-to-end risk management solutions across the buyer lifecycle
Analytics & Visualization: Build dashboards and reporting solutions that enable self-service insights and inform strategic decision-making
Requirements:
1–3 years of experience working with data and analytics
Strong quantitative and analytical skills, with hands-on experience in SQL and Excel
Experience building Tableau dashboards that enable insight discovery and data-driven decisions
Bachelor’s or Master’s degree in Statistics, Engineering, Mathematics, Operations Research, Risk Management, Industrial Engineering, or a related field
Strong communication skills with the ability to clearly convey insights to both technical and non-technical audiences
Nice to have:
Proficiency in Python
Exposure to machine learning frameworks or models
Prior experience in risk, fraud, or trust & safety analytics
Background in e-commerce, banking, fintech, or payments environments