Data Scientist Graduate (Global E-Commerce, Platform Governance) - 2027 Start

About the Team The team use the most advanced AI technology to combat various risks/violations in our E-commerce platform, maintain platform security, build a good e-commerce ecosystem, and empower business teams to improve work efficiency. We pursue the ultimate risk detection capability. The fairness and sustainability of the e-commerce ecosystem, high-quality content and merchandise are areas where we are constantly striving for improvement.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities 1. Governance Strategy & Risk Mining - Pattern Discovery: Deep dive into seller and listing behaviors to identify new abuse patterns. - Strategy Construction: Translate insights into executable governance strategies using Rules, Thresholds, and Risk Scores. Quickly deploy tactics to mitigate sudden attacks. - Practical Machine Learning: Develop agile, offline models (e.g., XGBoost, Random Forest, Anomaly Detection) and use Clustering to uncover organized bad-actor syndicates that simple rules might miss. 2. Metric System & Dashboard Construction - North Star Definitions: Define and standardize core metrics for Seller and Listing Governance, such as "Low-Quality Listing Rate," "Listing Violation Rate," and "Bad seller On-boarding rate“ - Dashboarding: Build and maintain comprehensive data dashboards (using internal tools) to visualize risk trends, strategy performance, and daily operational status. - Automated Monitoring: Design alert systems that automatically flag anomalies in the data . 3. Performance Tracking & Root Cause Analysis - Strategy Evaluation: Continuously monitor the Precision and Recall of governance strategies. Analyze false positives to minimize impact on good sellers. - Deep-Dive Analysis: When core metrics fluctuate (e.g., AIGC impact, GMV drops or complaint rates rise), conduct rapid root-cause analysis to determine if it is caused by governance interventions or external factors.