Staff Data Analyst, Coupang Pay

About the role

Coupang Pay provides payment experiences across Coupang's commerce ecosystem. Its Data Analytics team works with Product, Business, Data Science and Engineering to build data foundations, understand business performance and support data-driven decisions. The Staff Data Analyst combines strong technical analytics capabilities with sound business judgment, going beyond reporting to independently identify problems, analyse them in depth and recommend actions.

Key responsibilities

• Own key payment metrics, data marts and Tableau dashboards to give accurate, scalable visibility into business and product performance.
• Run deep-dive analyses to diagnose problems, find drivers and opportunities, and propose actionable recommendations.
• Analyse payment funnels, customer behaviour, payment methods, conversion and transaction success.
• Partner with Product and Business teams to define OKRs, spot analytical opportunities and influence decisions.
• Support A/B testing and experimentation, including metric design, experiment readouts and interpretation of business impact.
• Fill gaps in metrics and data by designing reusable datasets, analytical frameworks and self-service solutions.
• Communicate findings clearly to business, product and leadership stakeholders.
• Explore new analytics technologies, including LLM/Generative AI, to improve analytical depth and productivity.

Required profile

• 4+ years of experience in data analytics, product analytics, business analytics or a related quantitative role.
• Ability to structure ambiguous business problems and carry out rigorous, in-depth analysis.
• Strong business judgment, turning data into insights, recommendations and measurable actions.
• Experience defining metrics and supporting experimentation or A/B testing.
• Professional proficiency in English and/or Chinese, written and spoken.

Required skills

• Advanced SQL and experience with large-scale datasets and data marts.
• Tableau or similar BI/visualization tools.
• Preferred: Python, Spark/Hive, Redshift, Airflow; statistical analysis, experimental design and causal inference; LLM/Generative AI in analytics.

The recruitment process involves an application review, a phone interview and an onsite or virtual onsite interview. The position is full-time regular with a 12-week probation period, which may be skipped, shortened or extended.