Staff Data Scientist (Selection Technology)

About the role

Coupang is expanding its presence in Taiwan and is looking for a Staff Data Scientist to join its Selection technology team. The role sits at the intersection of product, operations, engineering and business, and focuses on applying AI and AI agent research to enrich product data, brand and manufacturer information, data mining and big data management. It suits someone who can build production solutions from scratch or improve existing ones.

Key responsibilities

• Design next-generation selection data mining systems at scale, covering extraction, query-based enrichment and dynamic product information from big data sources, using agentic and automated workflows
• Influence metric definition and raise standards on quality, revenue prioritization and opportunity capture
• Set the technical direction for evolving successful methods and models into scalable, cost-effective systems
• Design and develop statistical metrics and experiments to guide the selection strategy
• Research and analyze data to inform model development, using multi-modal LLMs and classical statistics and ML
• Work with product, engineering and business teams to turn ambiguous requirements into practical solutions
• Analyze launched solutions to measure outcomes and identify improvements
• Act as a cross-organization thought leader on AI and on evaluation and label quality issues

Required profile

• Bachelor's or Master's degree in mathematics, statistics, computer science, engineering or another quantitative discipline
• 8+ years of relevant experience in industry or academia
• Hands-on experience with statistics and ML fundamentals applied to production systems
• Ability to solve ambiguous problems and design data science solutions independently
• Excellent written and verbal communication with technical and business stakeholders

Preferred qualifications

• Production experience with LLMs and agentic systems
• Ability to model ambiguous business and operational problems at the right level of abstraction
• Systems thinking: pipelines, LLM-embedded workflows, human-in-the-loop workflows and hybrid agentic pipelines
• Advanced proficiency with Python, TensorFlow and PyTorch, used together with LLMs
• Deep understanding of e-commerce and ability to deploy advanced models in production

The recruitment process consists of an application review, a phone interview and an onsite (or virtual onsite) interview, followed by an offer. The posting may close early if all openings are filled.