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.