Anti-Fraud Analyst
We're looking for a strong, product-minded Antifraud Analyst who can work end-to-end and make calls independently. This isn't a "run the report and hand it off" role. You'll own the fraud detection layer - understanding the mechanics, building new controls from scratch, and constantly asking how do we make this better.
If you've spent time thinking about fraud systems the way a product manager thinks about a feature - you'll fit right in.
Your Future Responsibilities Await:
Design, build, and maintain data pipelines for fraud detection
Develop and optimize SQL-based data transformations for large-scale datasets
Ensure data quality, consistency, and integrity across antifraud systems and datasets
Build and maintain feature tables for fraud rules and scoring models
Work with streaming and event-based data (e.g., transactions, logins, device signals)
Optimize query performance and data models for high-volume data (millions+ records)
Develop, implement, and maintain fraud detection rules (SQL / rule engines)
Analyze fraud patterns (ATO, card fraud, onboarding fraud, etc.) and translate them into data-driven controls
Monitor rule performance (false positives / false negatives) and continuously improve detection logic
Perform deep-dive analysis of fraud cases and emerging patterns
What we expect from candidate:
Strong SQL expertise
Attention to detail and data accuracy
Ability to communicate findings to both technical and non-technical stakeholders
Ownership mindset and proactive approach
If you've spent time thinking about fraud systems the way a product manager thinks about a feature - you'll fit right in.
Your Future Responsibilities Await:
Design, build, and maintain data pipelines for fraud detection
Develop and optimize SQL-based data transformations for large-scale datasets
Ensure data quality, consistency, and integrity across antifraud systems and datasets
Build and maintain feature tables for fraud rules and scoring models
Work with streaming and event-based data (e.g., transactions, logins, device signals)
Optimize query performance and data models for high-volume data (millions+ records)
Develop, implement, and maintain fraud detection rules (SQL / rule engines)
Analyze fraud patterns (ATO, card fraud, onboarding fraud, etc.) and translate them into data-driven controls
Monitor rule performance (false positives / false negatives) and continuously improve detection logic
Perform deep-dive analysis of fraud cases and emerging patterns
What we expect from candidate:
Strong SQL expertise
Attention to detail and data accuracy
Ability to communicate findings to both technical and non-technical stakeholders
Ownership mindset and proactive approach