(Senior) Data Analyst, Zalopay (Risk)

The risk management team at Zalopay consists of highly motivated team players who are dedicated to building Zalopay as the most trusted financial service and the best against bad actors in the Vietnamese fintech market. By developing and adopting advanced tech-driven prevention mechanisms/solutions while focusing on user growth and customer experience, we aim to make risk management capability a core and key differentiation of Zalopay compared to other competitors. This helps our business grow sustainably and provide affordable services to all Vietnamese people.

How will you make an impact?

We are looking for a savvy, motivated, team-oriented Data Scientist to join our Risk Data Science team. The team is responsible for bringing insights from data to assess and manage multiple financial risk exposures (e.g., promotion abuse, ATO, KYC fraud, payment fraud), as well as developing and maintaining controls, strategies, solutions, and experiences related to the end-to-end management of these exposures.

The hire will be responsible for the full life-cycle of data product (i.e., from problem identification, to data product design & development, deployment, monitoring & optimization in production) of our Risk Data Solutions & Analytics. Day-to-day duties include data analysis, monitoring and forecasting, creating the logic for and implementing risk rules and strategies; and communicating with stakeholders to ensure we deliver the best possible customer experience while meeting loss rate targets.

What will you do?

• Participate in creating risk metrics, building dashboards by data visualization tools to monitor & identify abnormal user activities, app usage and fraudulent attempts (e.g.., promotion abuse, card payment fraud, account take over, etc.);
• Do exploratory data analysis to deep dive into cases of suspicious abuse or fraud (e.g., app & device info, installation and registration behavior, payment transaction details, etc.) and abnormal activities to find out fraudster or abuser behaviors;
• Work closely with Risk Strategy team, Risk Data Science team, Product team on analyzing and tracking impact & effectiveness of risk rules/policies/products/solutions (coverage, false-positive, drop-off rate of challenge) and propose actionable insights & plans to enhance them;
• Follow up the efficiency of your recommendations & adapt to different conditions;
• Work closely with Risk Data Platform team to ensure accurate and high-quality data is collected and analyzed on a consistent basis;
• Support to establish & develop post-mortem analysis and reporting for multiple aspects of Risk management including but not limited to promo campaigns, payment, wallet risks