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TikTok Shop - Ecommerce Anti-Fraud Data Scientist

company
TikTok
location
Singapore
posted
28 May
  • **Responsibilities**
  • About the Team As part of the Governance and Experience (GNE) organization, our Risk Control and Security team safeguards TikTok Shop’s global marketplace for users, sellers, and creators. We blend data-driven insights, policy design, and technical innovation to combat fraud while preserving a seamless user experience.
  • The Ecommerce Anti-Fraud Data Scientist role sits at the intersection of defining success metrics system, risk analytics, and cross-functional collaboration to monitor and mitigate fraudulent activities. Responsibilities
  • Define, standardize and monitor key performance metrics, building robust reporting models for effective tracking, evaluation, and continuous improvement
  • Conduct deep-dive RCA for fraud metric anomalies, collaborate with product/algo/engineering teams to optimize detection mechanism, and deliver actionable mitigation actions.
  • Design A/B experiments to evaluate model/strategy effectiveness, calculate ROI of anti-fraud initiatives, and scale high-impact solutions across global markets.
  • Leverage AI driven approaches to build and iterate scalable tooling to facilitate monitoring and analytics.
  • Lead cross-functional projects to address findings and present insights to key stakeholders and manage timeline of key projects.
  • **Qualifications**
  • Minimum Qualification(s):
  • Bachelor’s degree or above in Mathematics, Statistics, Computer Science, Business Analytic, or related fields (or post-graduation experience in data modeling/analysis).
  • Proficient in SQL and Tableau; skilled in Python/R for data analysis, model building, and visualization.
  • Strong ability to process complex datasets, identify fraud patterns, and translate insights into business actions.
  • Strong problem-solving skills to effectively address evolving fraud challenges.
  • Preferred Qualification(s):
  • Ecommerce anti-fraud experience (e.g., transaction fraud detection, ATO prevention) and GNE-related experience is a strong plus.
  • Global market analysis experience or cross-regional project leadership experience.
  • Experience with ML model lifecycle management (training, deployment, monitoring) and A/B experiment design for risk initiatives.
  • Experience with AI based analytics tooling.

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