Vacancy details
This is a private vacancy. Company details stay confidential until InVault confirms a serious candidate fit.
- Status
- Active
- Date posted
- 2026-11-15
- Open until
- 2027-02-13
- Employment type
- Full-time
- Source-listed languages
- Not specified
- Language requirement
- No mandatory language inferred
- Work arrangement
- Remote
- Physical workplaces
- Not specified
- Applicant eligibility
- United States
Overview
Own data-led fraud risk strategies for consumer financial accounts, focusing on login, recovery, device trust, profile changes and mobile-wallet provisioning. Analyze fraud losses and good-customer friction while shaping monitoring, automation and decisions with technology, operations and compliance teams.
Requirements
- At least five years directly managing authentication fraud risk strategies, including device and login risk, account recovery and profile updates.
- Deep understanding of account takeover, scams and social engineering methods and controls.
- Proficiency with SQL and Python for fraud portfolio analysis.
- Experience using AI tools, LLMs or workflow automation to improve fraud detection and operational decisions.
- Strong analytical ability to investigate behavioral patterns and measure fraud-loss and false-positive impacts.
- Clear cross-functional communication and ownership of risk strategy execution.
Responsibilities
- Develop and maintain authentication risk strategies to prevent takeover and scams.
- Set the roadmap for authentication analytics, tools and operational controls.
- Investigate fraud patterns with SQL and Python and improve monitoring coverage.
- Design and maintain device, login and recovery risk alerts and escalation logic.
- Integrate suitable AI-driven capabilities into authentication decision workflows.
- Use graph or network analysis to identify coordinated fraud rings while reducing false positives.
- Coordinate fraud incident investigation with engineering, product, operations and AML teams.
Conditions
- Full-time fully remote position for candidates located in the United States.
Tech stack
- SQL
- Python
