Anti-Fraud Analyst

Summary

Salmon is a technology-driven financial company building a banking and lending platform across Southeast Asia. The Anti-Fraud Analyst will own fraud and abuse detection across loyalty, cashback, credit, promotional, and referral programs by investigating suspicious patterns, analyzing financial impact, and developing permanent monitoring controls.

Responsibilities

• You'll be the dedicated fraud and abuse analytics owner for loyalty, cashback, credit, and referral programs across Salmon Bank
• You'll work directly with Risk, Product, and business teams — moving from a suspicious pattern to a tested hypothesis, an investigation, and a permanent monitoring rule
• The schemes you catch and the controls you build directly shape how much abuse costs the business, and how fast we close each gap
• Monitor transactions and customer behavior across cashback, promo, referral, and credit products to catch abuse patterns as they emerge
• Build and maintain SQL/Python-based reports and monitoring across large transactional datasets
• Form and test hypotheses on potential abuse schemes, then investigate flagged cases and assess their financial impact
• Calculate the economics behind each case — potential and actual losses, revenue impact, cost of abuse — to prioritize what gets fixed first
• Work with business and product teams to close the gaps: propose changes to product terms, promo rules, or cashback mechanics
• Turn every closed case into a permanent alert or trigger, and revisit past cases on a regular basis to check whether the pattern has returned

Skills

• Experience investigating and preventing abuse in banking or financial programs — cashback, credit cards/credit lines, promotions, referral programs, loyalty programs, or quasi-cash/transaction abuse
• You don't need to have covered every category above — what matters is hands-on experience building continuous monitoring, not one-off analysis
• Strong SQL and Python (or equivalent scripting), comfortable working directly with large transactional databases
• A track record of turning a hypothesis into a working monitoring system, not just a one-time report

Qualifications

Must Haves

• Experience investigating and preventing abuse in banking or financial programs — cashback, credit cards/credit lines, promotions, referral programs, loyalty programs, or quasi-cash/transaction abuse
• You don't need to have covered every category above — what matters is hands-on experience building continuous monitoring, not one-off analysis
• Strong SQL and Python (or equivalent scripting), comfortable working directly with large transactional databases
• A track record of turning a hypothesis into a working monitoring system, not just a one-time report

Benefits

• Fully remote work with core collaboration hours from 12:00 to 6:00 PM Manila time (UTC+8)
• Company-provided tools and equipment
• Medical insurance support for you and your family through co-funding or reimbursement, depending on your location and subject to policy limits
• Access to an internal mental health support specialist
• 22 vacation days, Philippine public holidays, and 15 sick days
• Opportunities to learn and share your expertise through internal expert meetups, external conferences, speaking opportunities, and industry publications
• Company-sponsored trips to Manila to meet and work with your team in person
• High-performing teams can earn a dedicated beach house week in Southeast Asia