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Staff Data Analyst

Coupang

Staff Data Analyst

Coupang

Taipei, Taiwan

·

On-site

·

Full-time

·

1w ago

Required Skills

SQL

Data Analysis

Hadoop

Apache Spark

Presto

Power BI

Tableau

Description

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did I ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar commerce industry. We are one of the fastest-growing retail companies that established an unparalleled reputation for being a leading and reliable force in the commerce industry.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. At Coupang, every day is filled with the excitement of building, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and challenge traditional tradeoffs. Join Coupang now to create an epic impact in this always-on, high-tech, and hyper-connected world.

  • Position: Staff Data Analytics
  • CX

As a product analyst, you will be responsible for providing reports and insights that aid in management to ensure top-notch customer experience. By collecting the tens of billions of data points that are created as millions of customers use Coupang’s services, Product Analytics creates meaningful insights, seeks answers to complex business questions, and enables a better understanding of customer behavior.

What You Will Do:

Create and provide new customer experience metrics and insights to ensure the best shopping experience for our customers.

Collaborate with product managers, designers, program managers, engineers, and other stakeholders to make data-driven decisions.

Create and manage weekly/monthly/quarterly business reports and work together with other teams to capture quality insights and present them to our stakeholders and leadership.

Expert thought leadership as an ecommerce and fulfillment service analyst.

Qualifications :

Experiencing working in Fraud domain is a plus

Expert SQL knowledge, with 6+ years’ work experience in data analytics

Experience in providing clear and actionable plans by analyzing data and insights

Ability to take work into your own hands with a sense of responsibility and exercise judgment to act in fast-paced and dynamic environment

Great ability to think critically and solve nonstructural problems

Strong communication skills to share analysis results clearly and concisely

Experience with big data tools like Hadoop, Spark, and Presto

Experience with BI tools like Power BI or Tableau:

Bachelor’s degree in statistics or computer engineering or equivalent experience

Preferences :

Experience with Python and R/SAS, or other statistical packages

Experience in working with version control (Git, SVN, etc.)

Well diverse in or comfortable with learning new modern data tools

Master’s degree in statistics or engineering or equivalent experience

Experience analyzing e-commerce and customer behavior logs

Strong English skill (both verbal and written) is a plus

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About Coupang

Coupang

An e-commerce platform that offers a wide variety of products, including apparel, electronics, and home goods.

10,001+

Employees

Seoul

Headquarters

$109B

Valuation

Reviews

2.5

9 reviews

Work Life Balance

2.1

Compensation

2.8

Culture

2.4

Career

3.2

Management

1.9

25%

Recommend to a Friend

Pros

Growth opportunities and career advancement

Good compensation and timely pay

Remote work flexibility

Cons

Poor work-life balance and long hours

Toxic management and controlling behavior

Poor working conditions and workplace safety

Salary Ranges

1 data points

Principal/L7

Senior/L5

Principal/L7 · Data Scientist L7

0 reports

-

total / year

Base

-

Stock

-

Bonus

-

Interview Experience

2 interviews

Difficulty

4.0

/ 5

Offer Rate

50%

Experience

Positive 0%

Neutral 50%

Negative 50%

Interview Process

1

Application Review

2

Recruiter Screen

3

Behavioral/Culture Fit Interview

4

Coding Interview

5

Technical Interview

6

Final Round

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit