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Risk Analyst (SQL), Card Payment Fraud

51 minutes ago
Thailand, Vietnam, Australia, New Zealand, Asia, Taiwan, Hong Kong
Full-time
Mid Level
Data Analyst
Data Science and Analytics
Feature Engineering Machine Learning SQL
Apply Now
Binance

Binance

Binance operates as a leading blockchain ecosystem and digital asset exchange, integrating digital technology with financial services to facilitate the trading and management of cryptocurrencies.

Capital Markets
5K-10K
Founded 2017
$10M raised
View All Jobs 230

Description

  • Monitor card authorization flows in real time and flag suspicious activity across debit and credit card portfolios.
  • Design, test, tune, and deploy fraud detection rules and risk scoring strategies at the authorization decision point.
  • Investigate suspected fraud cases such as account takeover, counterfeit cards, stolen cards, card-not-present fraud, and friendly fraud.
  • Determine root cause and take action through blocks, step-ups, or declines.
  • Track fraud losses, chargeback rates, approval rates, and other risk KPIs, and produce management dashboards and reports.
  • Work with dispute and chargeback teams on fraud-related chargebacks and network reason codes.
  • Partner with product, engineering, data science, and compliance teams to improve fraud models, tooling, and controls.
  • Stay current on emerging fraud typologies, BIN attacks, enumeration/testing attacks, and organized fraud rings.

Requirements

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

Benefits

  • Competitive salary and company benefits.
  • Work-from-home arrangement, depending on the business team and role nature.
  • Opportunity to work with world-class talent in a global organization with a flat structure.
  • Autonomy in a fast-paced, innovative environment.
  • Career growth and continuous learning opportunities.

Interested in this position?

Apply directly on the company website

Apply Now

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