Risk & Fraud Analyst

================================================================ WHY THIS ROLE EXISTS ================================================================ HitPay's fraud surface spans card chargebacks across multiple acquirers, non-card rails (PayNow, FPX, QRPH, GCash, TouchnGo, etc.), partner onboarding fraud, and the post-transaction tail that pre-tx vendors don't catch — across SG/MY/PH/HK/AU/US. We've built an automated detection stack that does the sweeping. What we need is a human in the loop who can investigate every exception, decide what's real, action it, and extend the toolset when a new fraud pattern shows up. This is not a queue-clearing role. The automation produces the queue. You bring the judgment, the partner conversations, the scheme and bank coordination, and the next piece of automation. ================================================================ WHAT YOU'LL OWN ================================================================ Daily investigation of every fraud and risk exception surfaced by the automated stack: - Post-tx fraud signals across all acquirers and rails - Bust-out, mule-ring, scam-proceeds, payout-redirect, and ATO patterns - ATV outliers, chargeback spikes, reserve adequacy, partner abandonment - Onboarding red flags surfaced before payments are enabled Chargeback and dispute lifecycle: - Read a dispute and tell us in 60 seconds whether it's first-party fraud, true fraud, or a real business having an outlier month - Represent/defend where it's worth defending; concede where it isn't - Spot the merchant whose chargeback curve is about to breach scheme thresholds before it does Decision and action on every flag: - Payment/payout status decisions (suspend, hold, offboard, retain with monitoring) - Reserve adjustments and reserve adequacy calls - Partner outreach for business-model clarification when a pattern looks off - Coordination with scheme risk teams (Visa/Mastercard), acquirers, and partner banks - Closing every exception with a documented, audit-ready rationale Tooling (this is the multiplier): - When you see a fraud typology the current stack misses, extend it or build a new detector for it - Backtest every rule change against labeled good/bad cohorts before it goes live - Every piece of automation you write is one fewer human-hour the team burns per week — that's the job ================================================================ WHO YOU ARE ================================================================ Payments risk and fraud background, non-negotiable: - 4+ years in payments/fintech fraud + risk ops, scheme-side fraud ops, or acquirer/PSP merchant-risk - You've personally worked chargebacks and disputes end to end — not just triaged them - Working knowledge of card scheme dispute frameworks (Visa VCR / Mastercard dispute rules), chargeback/fraud monitoring programs (VDMP/VFMP, ECM/EFM), reserves, and merchant underwriting risk - You can read a chargeback dispute, an unusual transaction pattern, or a partner's website and tell us in 60 seconds whether the partner is a fraudster cashing out stolen cards, a launderer with a real-looking storefront, or a real business having a good month — and which signals separate them - Exposure to non-card rail fraud (real-time payments, QR, wallet) is a strong plus Technical, non-negotiable. You must be technical enough to: - Query the data warehouse directly — write your own SQL against Snowflake, no analyst middleman. You'll be doing this every day. - Think in rules and thresholds — translate a fraud pattern you've spotted into a concrete, testable detection rule (signals, thresholds, edge cases, expected false-positive rate) - Backtest before shipping — every rule change runs against labeled good and bad cohorts before it goes live. No exceptions. If you don't know how to set up a backtest, you're not ready for this role. - Run and extend the existing automation stack — our detection skills are built on Claude Code. You inherit them on day one and use them daily. - Build