Director, Fraud Strategy & Operations

Payactiv•Milpitas, CA

8d•Onsite

About The Position

The Director, Fraud Strategy & Operations will serve as an operational partner to the VP of Consumer Banking, Payments and Fraud, supporting day-to-day execution of fraud programs across Payactiv’s consumer banking and payments ecosystem, including credit, debit, and prepaid cards. The role owns the real-time decisioning logic for the card portfolio, using data analytics to prevent fraudulent transactions while minimizing declines of legitimate transactions. The position involves designing, implementing, and optimizing fraud rules; testing and tuning rules against historical traffic; analyzing transaction data to identify emerging fraud patterns; and balancing fraud prevention, customer experience, and business performance. The role also links data across EWA transfers, direct deposits, and card transactions to identify account takeovers, and incorporates external merchant risk data into decisioning strategies. This is an onsite position, five days per week at the Milpitas office.

Requirements

4–7+ years of experience in fraud strategy and operations.
Deep experience authoring rules on real-time decisioning platforms and measuring relevant KPIs with appropriate trade-offs.
Hands-on experience with SQL and Python.
Strong technical knowledge of the ISO 8583 messaging standard and the card authorization lifecycle.
Good organizational and execution skills, with the ability to manage multiple priorities.
Experience working cross-functionally in demanding environments.
Analytical mindset and attention to detail.

Responsibilities

Author complex, multi-factor fraud rules using real-time decisioning platforms and transaction data.
Manage the lifecycle of fraud rules, including auditing legacy rules, retiring stale logic, resolving rule overlap, and maintaining efficient decisioning.
Test new rules in shadow mode against 30 days of historical traffic and assess their likely impact on legitimate users.
Justify rules with data-backed cost-benefit analysis and develop dynamic rules that adapt to individual user behavior.
Use SQL and Python for cluster analysis and detection of emerging fraud patterns.
Identify potential carding attacks and implement temporary circuit-breaker rules when needed.
Link EWA transfer, direct deposit, and card transaction data to identify account takeovers.
Incorporate external merchant risk data into rules, applying appropriate levels of scrutiny to merchants with different risk profiles.
Optimize false-positive rates and respond quickly to fraud-loss increases in specific transaction categories.
Avoid unnecessary declines of high-value transactions unless the risk score is sufficiently high.
Support day-to-day execution of fraud programs and initiatives across consumer banking and payments.