Fraud Prevention Strategy Owner
Zeta (company site, opens in a new tab)6+ yrsBengaluruOn-siteDirect career pageEst. 18–30 LPA
Posted 2h ago
Reach people at Zeta
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Zeta you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Mitigate fraud across outgoing payment rails including card payments and money transfers, focusing on various fraud typologies such as card-not-present, counterfeit, account takeover, and authorized push payment scams.
- Own the fraud rule lifecycle: diagnose emerging fraud patterns within 24 hours, deploy containment rules, maintain rule inventory, manage approval workflow, and perform regular performance reviews.
- Lead analytics, automate fraud operations, prioritize fraud reduction roadmap based on exposure and customer impact, and manage incident response including communication and post-mortem documentation.
Minimum Requirements
- Minimum 6 years experience in fraud strategy or analytics within US banks, card issuers, acquirers, neobanks, or payments companies.
- Hands-on experience with production fraud rules engines (e.g., Featurespace, Feedzai, SAS Fraud Management, FICO Falcon) including authoring and tuning rules.
- Strong SQL and Python skills for back-testing, loss sizing, and dashboard creation without dependency on data teams.
- Working knowledge of US payment rails fraud patterns (card networks, ACH, real-time/P2P payments) and Reg E compliance obligations.
Ideal Candidate Profile
- Experienced in managing end-to-end fraud rule lifecycle with measurable impact on reducing fraud losses and false positives.
- Proficient in applying ML/AI technologies to fraud prevention, having implemented, tuned, or retired model-driven controls.
- Capable of balancing fraud reduction with operational costs and customer friction, and skilled at automating manual workflows for fraud analysis and reporting.