Staff, Data Scientist (Growth Analytics)

Company Introduction

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 from the ground up. We are one of the fastest-growing commerce companies that established an unparalleled reputation for being a leading and reliable force in South Korean commerce.

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. We are all entrepreneurial, surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, 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 break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

 

Role Overview 

 

Our Analytics team has a mission to power the growth of Coupang through data-driven insights. We are a team of creative problem solvers with a passion to deliver innovative business solutions. The team leverages big data to empower business decisions and deliver insights, metrics and tools to drive customer engagement, retention and business growth. As the growth engine within one of the largest and fastest growing e-commerce platforms on the planet, Coupang’s analytics team offers countless ways for an ambitious data scientist to make an impact. 

 

Key Responsibilities 

 

• Build machine learning models, perform proof-of-concept, experiment, optimize and deploy your models into production. 

• Improve the analytical skillsets by adopting AI driven solutions. 

• Design and implement causal inference methodologies (e.g., RCTs, DiD, RDD, IV methods) to measure true incremental impact of marketing initiatives and product changes 

• Develop and deploy causal models that account for selection bias, confounding factors, and treatment heterogeneity in production environments 

• Establish scalable, efficient, automated processes for causal inference analysis, including experimental design, power calculations, and sensitivity analyses 

• Work with cross-functional teams to identify business opportunities where causal questions are critical, translating business problems into causal identification strategies 

• Analyze large-scale structured and unstructured data to isolate causal effects from correlational patterns; develop deep-dive analyses to drive customer engagement and retention 

• Design rigorous experimental and quasi-experimental frameworks to test product ideas and marketing strategies with clear identification of causal parameters 

• Create robust counterfactual analyses and develop methodologies to estimate treatment effects in observational settings 

• Communicate findings to senior leaders, distinguishing between correlation and causation, and evangelize evidence-based business decisions 

 

Basic Qualifications 

 

• Master's degree in a quantitative field - Economics, Statistics, Computer Science, Mathematics, Engineering or related fields 

• Strong programming skills in Python or R with experiences including causal inference libraries (e.g., DoWhy, CausalImpact, EconML, CausalML) 

• Advanced SQL skills for complex data manipulation; experience researching and manipulating large datasets 

• 8+ years working experience designing and analyzing experiments, natural experiments, observational studies and causal inference methodologies in industry settings 

• 8+ years working experience in the engineering teams that build large-scale ML-driven user-facing products 

• Experience with state of the art ML modeling techniques and approaches 

• Hands-on experience training and applying models at scale. 

• Demonstrated expertise in causal identification strategies, potential outcomes framework, and graphical causal models 

• Experience with propensity score methods, instrumental variables, difference-in-differences, synthetic controls, and other causal techniques 

• Ability to effectively communicate complex causal concepts and findings to technical and non-technical stakeholders 

• Self-starter who takes initiative to identify and address potential sources of bias and confounding 

• Outstanding team player with a rigorous scientific mindset focused on identifying true causal effects 

 

Preferred Qualifications 

 

• Hands-on experience adopting LLM models to analytical space, with agent building and adoption. 

• Experience with manipulating massive-scale customer and clickstream data for causal analysis 

• Deep expertise in causal machine learning methods (meta-learners, causal forests, orthogonal ML) 

• Experience with heterogeneous treatment effect estimation and personalized interventions 

• Experience designing and analyzing geo-experiments, switchback tests, and other complex experimental designs 

• Knowledge of Bayesian approaches to causal inference and uncertainty quantification 

• Excellent communication skills, with ability to explain causal identification strategies and limitations to different audiences, including executives 

• Experience implementing causal inference methods in production systems for real-time decision making 

• Publication record or contributions to the field of causal inference 

• Experience in working on, backend and ML systems for large-scale user-facing products, and have a good understanding of how they all work. 

 

Recruitment Process and Others

Recruitment Process

 

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer

• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.

• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

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.

• Hiring may be restricted in case the legal qualifications required for hiring and work performance is not met.

• This is a full-time regular position and includes 12 weeks of probation period; provided, however, the probationary period may be either skipped, shortened or extended if necessary for business purposes.

Privacy Notice

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice is located below.

https://privacy.coupang.com/en/land/jobs/

Document Return Policy (This notice MUST be included in a job posting in Korea only to comply with the Fair Hiring Procedure Act.)

1. This notification is given pursuant to Article 11 (6) of the Fair Hiring Procedure Act.
2. A job applicant, who has applied but not been finally selected for a position at Coupang (the “Company”), may request the Company to return his/her hiring documents submitted pursuant to the Fair Hiring Procedure Act. However, this will not apply where the hiring documents were submitted via the website of the Company or e-mail, or where the job applicant submitted those documents voluntarily without a request from the Company. In addition, if the hiring documents were destroyed due to a natural disaster or any other reasons not attributable to the Company, such documents will be deemed to have been returned to the job applicant.
3. A job applicant who wishes to request the return of his/her hiring documents pursuant to the main sentence of paragraph 2 above should fill out a “Request for Return of Hiring Documents” [Annex Form No. 3 in the Enforcement Rule of the Fair Hiring Procedure Act] and submit It by email (recruitingops@coupang.com). In such case, within fourteen (14) days from the date of identifying the receipt of the request, the Company will send the hiring documents to the job applicant’s designated address via registered mail. Please be informed that the job applicant is required to pay the postage on the registered mail.
4. In preparation for a job applicant’s request for the return of hiring documents pursuant to the main sentence of paragraph 2 above, the Company shall retain the original hiring documents submitted by the job applicant for 180 days from the completion of the recruiting process. If no request is made until the end of this period, all his/her hiring documents will be destroyed immediately in accordance with the Personal Information Protection Act.
5. The above paragraphs 1 - 4 shall only apply when the labor-related laws of Korea govern the application. They are otherwise not applicable.

Equal Opportunities for All

Coupang is an equal opportunity employer. Our unprecedented success could not be possible without the valuable inputs of our globally diverse team.