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Salmon Group

Anti-Fraud Analyst

Posted 14 Days Ago
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Remote
Hiring Remotely in Georgia, USA
Entry level
Remote
Hiring Remotely in Georgia, USA
Entry level
Own fraud and abuse analytics across cashback, credit, promotional, and referral programs. Monitor transactions and customer behavior, investigate suspicious patterns, quantify financial impact, and collaborate with Risk, Product, and business teams to close vulnerabilities. Build SQL- and Python-based reports, alerts, and continuous monitoring systems that convert investigated cases into permanent controls.
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Salmon is a technology-driven financial company building a banking and lending platform across Southeast Asia, starting in the Philippines.

We combine global fintech expertise with deep local market knowledge to make financial services simple, accessible, and useful for millions of people across the region.

7M+ app downloads. 2M+ monthly active users. 7,000+ partner stores. US$310M+ raised from leading global investors.

Manila-based, globally distributed, and hybrid-first — our team spans 45+ countries.

If you want to solve complex problems at scale and impact how millions of people access and manage money, come build with us.

Southeast Asia's fintech moment starts here.

About the role:
You'll own fraud and abuse detection across our cashback, credit, promo, and referral mechanics — building the monitoring that keeps these programs profitable and safe.

What you'll do:

  • 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.

What you'll own:

  • 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.

What makes you a strong fit:

  • 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.

What we offer:

Ownership and flexibility

  • Fully remote work with core collaboration hours from 12:00 to 6:00 PM Manila time (UTC+8)

  • Company-provided tools and equipment

Health and time off

  • 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

Growth and team experience

  • 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

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