Lead - Fraud Risk Strategy

Job description

Job Summary: We are seeking a highly analytical and strategic Fraud Risk Manager/Lead to join our team. In this pivotal role, you will be responsible for designing, implementing, and optimizing fraud strategies for a leading global payments ecosystem. The ideal candidate will bring strong technical expertise in SQL and Python, coupled with a deep understanding of the payment fraud industry. You will play a critical role in managing fraud losses across Consumer-to-Consumer (C2C) and Consumer-to-Business (C2B) payment flows, while simultaneously improving payment authorization rates and ensuring a frictionless customer experience. Required Qualifications: Bachelor’s or Master’s degree in Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field. 3 to 6 years of hands-on experience in fraud strategy, specifically within Fintech, Digital Payments, E-commerce, or Payment Gateways. Demonstrated experience in designing and implementing fraud rules using transactional, behavioral, and third-party data. Strong proficiency in: SQL: Advanced querying, joins, aggregations, and performance tuning for massive transactional datasets. Python: Data manipulation (Pandas, NumPy), exploratory data analysis, and basic modeling; ability to productionize or hand over code to engineering teams. Strong analytical and problem-solving skills with the ability to translate data insights into actionable strategies that directly impact the bottom line Key Responsibilities: • Domain Expertise: Proven experience in the Payments Industry, specifically dealing with Transactional Fraud, Digital Wallets, Payment Gateways, and E-commerce fraud • Fraud Strategy & Mitigation: Design, implement, and manage robust fraud prevention strategies for C2C (peer-to-peer) and C2B (merchant checkout) payment products, as well as Debit Card portfolios (covering both Card Present and Card Not Present transactions). • Authorization Optimization: Analyze transaction data to improve payment authorization rates across various checkout flows (both branded and unbranded/guest checkouts) while keeping fraud losses within risk appetite. • Customer Experience (CX): Balance aggressive fraud mitigation with user experience by minimizing false positives (false declines) and reducing unnecessary friction for legitimate customers. • Data-Driven Investigation: Investigate suspicious transaction patterns, account takeovers (ATO), and payment anomalies to determine root causes and develop proactive statistical models/rules. • System & Rule Development: Design and deploy fraud rules within decision engines and workflow systems. Build comprehensive monitoring reports to track the performance of fraud strategies.