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Binance - Risk Analyst (SQL), Card Payment Fraud

Taiwan, Taipei5d ago

In Office Mid APAC Cryptocurrency Payments Financial Analyst Data Analyst SQL Data Analysis SAS Reporting Case Management Cross-functional Collaboration

Requirements

• 3+ years in card payment fraud risk, ideally on the issuer or card processor / issuer-processor side. • Solid understanding of the card payment lifecycle: authorization, clearing, settlement; the roles of issuer, acquirer, card network (Visa/Mastercard), and processor. • Familiarity with authorization message flows (ISO 8583), auth/decline codes, AVS, CVV, and 3-D Secure (3DS) / SCA. • Working knowledge of fraud typologies: card-not-present (CNP) fraud, account takeover (ATO), counterfeit/cloned cards, lost/stolen, BIN attacks, card testing/enumeration. • Experience with fraud detection / rules engines (e.g., Falcon, SAS, Feedzai, Featurespace, or in-house platforms). • Strong data analysis skills: SQL required; ability to interrogate transaction data and quantify fraud/risk trade-offs. • Understanding of chargeback lifecycle and network dispute reason codes. • Experience tuning real-time authorization rules and measuring fraud vs. false-positive trade-offs. • Exposure to machine learning fraud models and feature engineering for risk scoring. • Crypto card experience: familiarity with crypto-linked cards and crypto-to-fiat settlement at auth. • Knowledge of PCI-DSS and relevant regulatory/compliance requirements. • Industry certifications (e.g., CFE — Certified Fraud Examiner).

Responsibilities

• Real-time transaction monitoring: Monitor card authorization flows and flag suspicious activity across debit/credit card portfolios. • Fraud rule strategy: Design, test, tune, and deploy fraud detection rules and risk scoring strategies at the authorization (auth) decision point — balancing fraud capture rate against false-positive / decline rates. • Investigation & case management: Investigate suspected fraud cases (account takeover, counterfeit/cloned cards, stolen card, CNP fraud, first-party/friendly fraud), determine root cause, and take action (block, step-up, decline). • Loss & performance analysis: Track fraud losses, chargeback rates, approval rates, and key risk KPIs; produce dashboards and reporting for management. • Chargeback & dispute support: Work with dispute/chargeback teams on fraud-related chargebacks and network (Visa/Mastercard) reason codes. • Cross-functional collaboration: Partner with product, engineering, data science, and compliance to improve fraud models, tooling, and controls. • Emerging threat detection: Stay ahead of evolving fraud typologies, BIN attacks, enumeration/testing attacks, and organized fraud rings.

Benefits

• Shape the future with the world’s leading blockchain ecosystem • Collaborate with world-class talent in a user-centric global organization with a flat structure • Tackle unique, fast-paced projects with autonomy in an innovative environment • Thrive in a results-driven workplace with opportunities for career growth and continuous learning • Competitive salary and company benefits • Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)