Meet Matthew, Ian, and Saizy — Coupang Data team
Coupang makes business decisions based on data. To this end, Coupang has data experts designing Coupang's unique data systems and tools and has more professional experience using its own A/B system.
We met Data Engineer (DE) Matthew, Data Scientist (DS) Ian, and Data Analyst (DA) Saizy, who connect Coupang's business with customers through data. How are the three data positions collaborating within the Coupang’s data ecosystem?
Hello, thank you for having the interview. Would you please introduce yourself?
Matthew: Hello, I’m Matthew leading the Data Engineering team of the Data Platform organization. The team collects and processes data that affects Coupang's key business decisions and builds and operates big data infrastructures.
Ian: Hello, I’m Ian, a data scientist from Coupang Pay. My job is to develop a credit rating model for customers and to create an engineering environment where data scientists can work in better working conditions.
Saizy: Hello, I'm Data Analyst Saizy. I'm working on feature analysis related to customer experience. More simply, I analyze and provide data throughout the process of developing features to address customer pain points to ensure they are valid and efficient.
You are all in different teams, please tell us more about your team.
Matthew: The Data Platform organization is mainly divided into two teams; one working on ETL operations and data mart management based on massive internal data, and the other team creating infrastructures for various users, including data analysts, data scientists, and data engineers to analyze/process/schedule/visualize their data.
Ian: Our team takes care of making predictions on a variety of products related to Coupang’s different payment products. The product we are currently focusing on is PayLater, which is a BNPL (Buy Now Pay Later) service. Our job is to lower the delinquency rate by building Coupang’s own credit rating model based on data.
Saizy: The DA releases several features to improve Coupang's customer experience. As an analysis team, we help decision makers make data-driven decisions before and after the release of features.
Which Leadership Principle best describes your team’s culture?
Matthew: It's ‘Company-wide Perspective’. As I said, the Data Platform organization builds data platforms and big data infrastructures. We operate and improve systems by considering data analysts, data scientists, and data engineers as much as possible. Also, we do our work completely from the company-wide perspective. In other words, we design and build data and systems considering not only the needs of specific business domains but also company-wide impact and internal security.
Ian: It’s “Learn Voraciously” for our team. We develop great teamwork based on “learning.” Working with other teams, I learned and used a range of new modelling techniques which helped me to grow faster than ever before. We share a lot of insights with each other while discussing how to develop models in a way that can be well reflected in business.
Saizy: It’s ‘Wow the Customer’. Our organization focuses most on improving customer experience. We take a deep approach to various areas that affect our customers from the Coupang app home to the page where the order is completed. We are also testing various hypotheses and improving our customer experience in a strategic and logical way.
Coupang is a data-driven company, but what is the actual working method like? Please explain with real-world examples how Coupang uses data to improve customer experience and create innovation.
Matthew: Data marts and source data we provide have a significant impact on data-driven decisions. We review data points of key services and data marts at weekly Business Review meetings. Through the process, we analyze customer and system pain points and resource investments and make various decisions.