Anti-Fraud Strategy Expert

Professional Services • Full Time • Sheung Wan, Hong Kong, HK • 1w ago

Rapidly expanding Fintech company in HK, US, SG
SFC licensed corp - Type 1, 2, 4, 5, 6 & 9
Lead the mining and development of anti-fraud strategies for internet brokerage

Job Summary：

As an Anti-Fraud Strategy Expert, you will join our Risk and Compliance Technology team. You will be responsible for constructing and optimizing a real-time anti-fraud system that covers the entire user lifecycle, including account opening, deposits, trading, marketing campaigns, and withdrawals. Your goal is to leverage big data analytics and machine learning to accurately identify and intercept fraud ring attacks, fake account registrations, money laundering risks, and market manipulation – all while maintaining a seamless user experience

Job Responsibilities:

Strategy Development & Optimization: Lead the mining and development of anti-fraud strategies for internet brokerage scenarios. Design and maintain real-time risk rule engines targeting Account Takeover (ATO), Fake Accounts, Bonus Abuse, and Card-Not-Present (CNP) fraud

Data-Driven Insights: Perform deep-dive analysis on massive datasets using SQL/Python to uncover attack patterns and evolution trends of fraud syndicates. Produce regular, in-depth risk analysis reports.

Model Collaboration: Partner with Algorithm Team to integrate machine learning models (e.g.: anomaly detection, knowledge graphs, device fingerprinting) into the strategy pipeline to enhance automated detection capabilities

End-to-End Risk Planning: Participate in the requirements design and architectural review of the underlying anti-fraud system. Drive the improvement of risk infrastructure, including risk tag libraries, blacklists, and risk monitoring dashboards.

User Experience & Business Balance: Find the optimal balance between risk control and business growth (e.g.: account conversion rates and trading fluidity). Design tiered response mechanism to minimize friction for legitimate users

Cross-Functional Collaboration: Work closely with Product, Tech, Compliance (AML/KYC), and Operations teams to conduct risk assessments for new products/features and ensure rapid response to live risk incidents

Job Requirements:

Bachelor’s degree or above in Statistics, Mathematics, Computer Science, Financial Engineering, or a related quantitative field
3-5+ years of experience in anti-fraud strategy or risk management within Fintech, third-party payments, or top-tier brokerages
Proficiency in SQL with the ability to handle billion-level data scales
Skilled in Python or R for data analysis and feature engineering
Familiarity with mainstream Risk Rule Engines (e.g. Drools, Flink CEP) or third-party risk management platforms
Familiarity with internet brokerage workflows, cross-border capital compliance, and a high sensitivity toward market manipulation (e.g.: wash trading, matched orders)
Strong logical reasoning, high pressure tolerance, and the ability to handle emergency risk events. Excellent communication skills in both Chinese and English to thrive in an international team environment
Professional certifications such as CFE (Certified Fraud Examiner) or ACAMS (Association of Certified Anti-Money Laundering Specialists)
Hands-on experience in combating large-scale fraud rings or using graph Analysis (Social Network Analysis) for fraud detection
Knowledge of machine learning algorithm principles with a track record of successful deployment in production environments

We offer attractive remuneration package to the right candidates. Interested parties please send your current and expected salary by email.

Data collected will be used for recruitment purpose only.

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