Fraud Risk Manager

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.

Responsibilities:

• Domain Expertise: Proven experience in the Payments Industry, specifically dealing with Transactional Fraud, Digital Wallets, Payment Gateways, and E-commerce fraud.
• Fraud Strategy and 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 and Rule Development: Design and deploy fraud rules within decision engines and workflow systems. Build comprehensive monitoring reports to track the performance of fraud strategies.

Requirements:

• 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.