About the role
We are looking for a Fraud Analytics Manager to lead and scale our fraud prevention strategies across personal loans and credit cards. In this role, you will drive the design, implementation, and optimization of fraud detection models and strategies. You will work closely with other business areas, including product, data science, engineering, and operations, to stay ahead of emerging fraud threats.This role will report to the Lead Product Manager of US Cards.
What you'll be doing
Strategy Development: Design and implement end-to-end fraud detection strategies (first party and third party) for personal loans and credit cards across the product lifecycle (customer acquisition, account takeover/credit card transactions, and payments).
Data Analysis and Insights: Analyse usage patterns and trends to measure and optimize the effectiveness of existing fraud strategies, including balancing value from fraud prevention vs. opportunity cost of false positives. In addition, manage the suite of dashboards and tools to monitor key fraud metrics and quickly detect fraud attacks.
Fraud Operations: Work closely with operations to continue improving workflows and case management for fraud investigations and build out and enhance fraud operations processes.
Benchmarking: Participate in industry roundtables and events to research new fraud technologies and trends.
Your experience
Experience: 3+ years of experience in fraud analytics for unsecured lending products, ideally with credit cards; familiarity working with third-party fraud detection tools.
Technical Skills: Proficiency in SQL or Python for data analysis; familiarity with decision trees or other predictive modelling is a plus
Domain Knowledge: Familiarity with applicable laws and regulations that impact Zendable’s business including BSA, OFAC, GLBA, TILA including the Credit Card Accountability, Responsibility and Disclosure (CARD) Act of 2009, FCRA, UDAAP, FDCPA, ECOA, E-Sign, EFTA, and NACHA.
Education: Bachelor’s degree in a quantitative field (e.g., statistics, mathematics, economics, or data science).
Compensation
Offers Equity
