Fraud & Abuse Analytics Lead — Remote

Salmon Group; Georgia; Hybrid; USD 110,000 - 170,000; Full time

Benefits offered by this job

Fully remote

Core hours Manila TZ 12:00–18:00

Equipment provided

Health coverage

Mental health support

Vacation days

Company trips to Manila

Beach house week

Job summary

Salmon Group is seeking a remote fraud analytics specialist to own analytics across cashback, credit, promo, and referral programs. You will build and monitor continuous detection rules, quantify losses, and work with Risk and Product teams to close abuse gaps.

You will develop SQL/Python reports on large datasets, test hypotheses, and turn discoveries into permanent monitoring rules. The role emphasizes scalable monitoring and cross-functional collaboration in a global fintech context.

Qualifications

• Experience investigating and preventing abuse in banking or financial programs (cashback, credit, promotions, referrals).
• Hands-on experience building continuous monitoring systems and alerts.
• Strong SQL and Python skills, able to build and maintain scalable data reports.

Responsibilities

• Own fraud and abuse analytics for loyalty, cashback, credit, and referral programs across Salmon Bank.
• Collaborate with Risk, Product, and business teams to convert patterns into tested hypotheses and monitoring rules.
• Catch abuse patterns, quantify losses, and prioritize fixes based on financial impact.
• Design and test monitoring hypotheses, investigate flagged cases, and implement permanent alerts.
• Build and maintain SQL/Python reports across large transactional datasets.
• Propose changes to product terms, promo rules, or cashback mechanics to close gaps.
• Turn each case into a permanent alert and revisit past cases periodically.

Skills

SQL

Python

Fraud detection

Monitoring systems

Data analysis

Job description

Salmon Group is seeking a remote fraud analytics specialist to own analytics across cashback, credit, promo, and referral programs. You will build and monitor continuous detection rules, quantify losses, and work with Risk and Product teams to close abuse gaps.

You will develop SQL/Python reports on large datasets, test hypotheses, and turn discoveries into permanent monitoring rules. The role emphasizes scalable monitoring and cross-functional collaboration in a global fintech context.