Manager, Data Analysis at Coupang

Taipei, , Taiwan -

Full Time

Start Date

Immediate

Expiry Date

20 Jul, 26

Salary

0.0

Posted On

21 Apr, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, R, Tableau, PowerBI, Looker, Prompt Engineering, LLMs, A/B Testing, Regression Analysis, Hypothesis Testing, Data Analytics, Business Intelligence, Predictive Modeling, Team Leadership, Strategic Planning

Industry

Software Development

Description

Company Introduction Coupang is reimagining the shopping experience with the goal of wowing each customer from the instant they open the Coupang app to the moment an order is delivered to their door. Our services in Taiwan include “Rocket Delivery” which offers next-day delivery for a wide selection of items at affordable prices, “Rocket Oversea” which offers free international delivery on millions of best-selling products from Korea, the U.S., and beyond. We are looking for talents to help us lead Coupang’s expansion in Taiwan. This is an exceptional opportunity to become a part of Coupang’s growth in Taiwan and create a world where our customers wonder, “How did I ever live without Coupang?” Role Overview As the Senior Manager of Data Analytics, you will lead the intelligence engine for Coupang Taiwan’s Post-Purchase Experience, CS & Fraud. You will transform massive datasets into actionable strategies that reduce return defects, fraud, optimize customer service efficiency, and identify opportunities to improve return customer experience. You will lead a team of analysts to bridge the gap between "what happened" and "what we should do next." What You Will Do Strategic Insights: Lead the end-to-end analytics for the Returns and CS lifecycle. Identify root causes for high return rates (e.g., sizing issues, logistical damage, or fraud) and propose data-backed solutions. Predictive Modeling: Develop and oversee models to predict return propensity and customer lifetime value (CLV), helping the business proactively manage risk. Performance Measurement: Define and own the "North Star" metrics for the Taiwan CS organization, including First Contact Resolution (FCR), Net Promoter Score (NPS), and Cost per Contact. Stakeholder Influence: Act as a strategic partner to the PPE (Process, Policy & Engineering) and Logistics teams, using data to influence the product roadmap and operational SOPs. Team Leadership: Mentor and scale a team of high-performing data analysts, fostering a culture of technical excellence and business-first thinking. Dashboarding & Automation: Transition the organization from manual reporting to real-time, automated BI solutions (Tableau/Looker) that empower regional leads Basic Qualifications Experience：8+ years in Data Analytics, Business Intelligence, or Data Science (E-commerce or FinTech preferred). Technical Stack：Expert proficiency in SQL and Python/R. Deep experience with Tableau, PowerBI, or Looker, Prompt engineering, usage for LLMs for analytics. Statistical Skills：Strong grasp of A/B testing, regression analysis, and hypothesis testing. Leadership：3+ years of experience managing direct reports and leading cross-functional projects. Communication：Ability to translate "data-speak" into executive-level narratives in both English and Mandarin. Details to Consider This job posting may be closed prior to the stated end date for application if all openings are filled. Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process. Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. Privacy Notice Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/

Responsibilities

Lead the end-to-end analytics for the Returns and CS lifecycle to identify root causes for high return rates and fraud. Develop predictive models for customer lifetime value and define key performance metrics to influence operational strategies.