Monee Hiring! Full Time Fraud Risk Analyst, Strategy - Analytics - Promo Abuse in - Ricebowl

About The Team

As a Fraud Risk Analyst specializing in Promo Abuse, you will be responsible for safeguarding ShopeePay’s promotional budgets, vouchers, and cashback/coin ecosystems. You will analyze transaction patterns, identify vulnerabilities in marketing campaigns, and design proactive defense mechanisms against both casual exploiters and organized fraud syndicates (such as multi-accounting, fake merchant collusion, and bot attacks). This role sits at the intersection of data analytics, product optimization, and risk management.

Job Description

• Risk Assessment & Campaign Review: Review upcoming ShopeePay promotional campaigns, referral programs, and voucher mechanics to identify potential loopholes and fraud vulnerabilities before they go live.
• Fraud Detection & Pattern Analysis: Deep-dive into large-scale transactional, device, and behavioral datasets to identify emerging promo abuse trends, including app-cloning, SIM farming, fake merchant cash-outs, and self-referral chains.
• Rule & Policy Optimization: Design, implement, and tune real-time risk engine rules and velocity thresholds to block malicious actors while maintaining a seamless user experience for genuine customers.
• Cross-Functional Collaboration: Partner closely with Marketing, Product, Commercial Merchants, and Data Science teams to build scalable, automated features (e.g., advanced device fingerprinting, KYC triggers) that minimize promo leakage.
• Incident Response & Post-Mortem: Lead investigations into sudden budget drains or coordinated exploit incidents. Conduct root-cause analyses and implement immediate mitigation strategies to prevent recurrence.
• Reporting & Metrics Tracking: Define and track key performance indicators (KPIs) for promo abuse, such as Fraud ROI, False Positive Rates, and total prevented loss, presenting insights regularly to senior leadership.
  
  

Requirements

• Bachelor’s degree or higher in Computer Science, Engineering, Business Analytics, Information Technology, Finance, Statistics, or a related field.
• Proficiency in SQL is mandatory (ability to query complex, high-volume databases independently).
• Experience with Python or R for data analysis, data manipulation, or basic predictive modeling is highly preferred.
• Familiarity with data visualization tools like Tableau, PowerBI, or QlikSense is a plus.
• Strong analytical thinking, pattern recognition, and investigative skills. You should possess a "think like a fraudster" mindset to anticipate how a system or promotion can be exploited.
• Excellent communication and stakeholder management skills, with the ability to translate complex technical fraud findings into actionable business advice for marketing and product teams.