Straive - Manager/Lead - Fraud Prevention

Experience: 5-10 yrs

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.

• 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) payment products
• C2B (merchant checkout) payment products
• Debit Card portfolios (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)
• Reducing unnecessary friction for legitimate customers

Data-Driven Investigation:

• Investigate suspicious transaction patterns, account takeovers (ATO), and payment anomalies
• 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 fraud strategy performance

• 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 within:

• Fintech
• Digital Payments
• E-commerce
• Payment Gateways

Demonstrated experience in designing and implementing fraud rules using:

• Transactional data
• Behavioral data
• Third-party data
• Technical Skills:

SQL:

• Advanced querying
• Joins and aggregations
• Performance tuning for large transactional datasets

Python:

• Data manipulation (Pandas, NumPy)
• Exploratory data analysis
• Basic modeling
• Ability to productionize or hand over code to engineering teams