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Salary
≈ $26k – $63k per year (Estimated)
Location
In office (Taipei)
Seniority
Staff · 5+ years exp

Confirmed on the employer's own hiring board on Oct 19, 2026. First seen by Alion on Aug 12, 2026. Coupang scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Coupang is a leading South Korean e-commerce company founded in 2010 that operates one of the country's largest online retail platforms. The company is widely recognized for its specialized logistics network, known as "Rocket Delivery," which enables same-day or next-day fulfillment for millions of products. In addition to online shopping, Coupang has expanded its ecosystem into digital streaming with Coupang Play, food delivery through Coupang Eats, and international markets such as Taiwan.

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:

We're in search of a Staff Data Scientist to join our supply chain management technology team. This role is ideal for someone deeply passionate about applied research, AI/ML, and Operations Research, eager to collaborate across product, engineering, business, and operations to tackle the most complex challenges in supply chain management. The successful candidate will thrive in an interdisciplinary environment, adept at developing production solutions from scratch or enhancing existing ones, and will play a pivotal role in shaping and executing the vision for automating supply chain management.

What You Will Do:

  • Collaborate closely with cross-functional teams, including product, engineering, and business, to identify opportunities for enhancing our technology products, translating ambiguous business requirements into practical solutions.
  • Conduct comprehensive research and analysis to inform model development, establishing metrics and success criteria for evaluating solution effectiveness
  • Deliver data-driven solutions to support automated decision-making at scale, leveraging advanced Statistics, Machine Learning, and Operations Research techniques to optimize business processes and make data-driven decisions/predictions
  • Analyze/solve complex data problems using innovative methods, such as deep learning, and communicate findings to technical and non-technical stakeholders through clear and concise reports and presentations
  • Provide analysis for launched solutions to quantify outcomes based on real-world results, identifying areas for improvement and opportunities for future development

 

Basic Qualifications

  • Bachelor's/Master's degree in mathematics/statistics, computer science/engineering, industrial engineering, operations research, or any other quantitative disciplines, with 5+ years of relevant experience working in industry or academia
  • Hands-on experience in statistics/ML fundamentals and demonstrated experience in Python, SQL, and basic visualization tools (e.g., Tableau, Power BI)
  • Strong critical thinking skills and ability to solve ambiguous problems supported by solid knowledge of data science and machine learning fundamentals, with proven experience to formulate business problems to data science solutions 
  • Ability to conduct analysis independently for a business problem through data manipulation, hypothesis formulation, experiment design, and statistical analysis
  • Excellent written and verbal communication skills to effectively engage with technical and business stakeholders at all levels, including presentation development and delivery

Preferred Qualifications:

  • Strong ability to model ambiguous business and operational problems at the appropriate level of abstraction, with a focus on delivering practical solutions
  • Advanced proficiency with machine learning frameworks, tools, and languages such as Python, R, Java, TensorFlow, and PyTorch, with experience building ML/DL models to handle large-scale datasets
  • Proven experience in AI/ML-driven demand forecasting, lead time prediction, causal models, fulfillment rate prediction, with the ability to collaborate with ML Engineers and Data Analysts to optimize model development and deployment
  • Experience designing and implementing large-scale optimization solutions for complex business problems
  • Expertise in developing and deploying advanced algorithms, including decomposition methods, heuristics/metaheuristics, and hybrid methods
  • Familiarity with Big Data ecosystem (Spark, Hive, HBase) and SQL/NoSQL (Redis/MongoDB) for handling complex data transformations and analysis
  • A deep understanding of the e-commerce business domain and the ability to apply cutting-edge models into production environments, driving measurable results

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.

  • Coupang does not discriminate against disabled applicants or those with veteran status.
  • We are proud to offer equal opportunities for all applicants.

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