A growing digital payments environment needs sharp minds who can stay ahead of evolving fraud patterns. This role is built for someone who enjoys working at the intersection of data, risk, and product, turning complex transaction signals into clear, scalable protection strategies. You’ll play a central part in strengthening payment integrity while ensuring smooth, trusted experiences for users. This position focuses on designing and executing fraud and risk strategies that support long-term business growth while keeping financial exposure under control. The work blends analytical deep-dives, hands-on investigation, and close collaboration with technical teams to embed fraud prevention directly into systems and workflows. You’ll be expected to move fluidly between strategy development, data analysis, and operational execution, identifying emerging risks early and translating them into practical, automated safeguards.
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Build and drive end-to-end fraud and risk strategies, from identifying vulnerabilities through to design, testing, rollout, and ongoing performance evaluation
- Detect, investigate, and track suspicious or abnormal transaction behavior, identifying key drivers behind shifts in fraud trends and payment patterns
- Conduct detailed analysis of internal and external datasets, producing clear insights, reporting, and root-cause breakdowns of fraud and chargeback activity
- Partner closely with engineering and product teams to design and implement scalable fraud prevention systems that balance growth with protection
- Serve as a key point of contact for payment processors and external vendors, ensuring alignment on fraud controls, issue resolution, and system improvements
- Continuously refine detection approaches based on evolving fraud tactics and business needs
The right person combines strong analytical thinking with practical fraud expertise and a mindset geared toward problem-solving in fast-moving environments.
- 5+ years of professional experience, including at least 3 years focused on fraud and 1+ year in payments
- Experience working across multiple payment methods, ideally in e-commerce or digital transactions with multi-currency exposure
- Proven ability to investigate fraud cases and identify suspicious transaction behavior through hands-on analysis
- Strong SQL skills with the ability to independently work with large, complex datasets
- 3+ years of experience in data modeling for fraud detection, including anomaly detection, user risk scoring, and feature engineering
- Experience building and deploying machine learning models (Python or R; tools such as Sklearn, XGBoost, LightGBM, etc.) into production systems
- Familiarity with integrating models into automated risk or decisioning pipelines
- Background in roles such as Fraud Analyst, Risk Analyst, Data Scientist, Operations Specialist, or Product Manager
- Degree in Engineering, Computer Science, Statistics, Finance, or a related analytical field
- Strong ability to think like an attacker, anticipating how fraud can occur and proactively designing defenses
- Mandarin language skills are a plus
This role suits someone who thrives in complex, data-heavy environments and enjoys turning ambiguity into structured, scalable solutions. If you like digging into patterns, challenging assumptions, and building systems that prevent problems before they happen, this is a strong fit.
