Staff Data Scientist (Catalog)

This role works at the intersection of product, operations, engineering and business. The successful candidate will therefore 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 our mission to make our Catalog technology a competitive advantage.

What You Will Do:

• Design the next generation of Catalog systems that work at scale across extraction, query-based enrichment, dynamic product info like product highlights, defect reduction, etc. using agentic and automated workflows. You will influence metric definition and will raise the bar on quality, completeness, readability and accessibility.
• Set the technical direction for how we evolve existing successful methods and models into scalable, cost-effective systems that can impact the quality of tens of millions of listings.
• Conduct comprehensive research and analysis to inform model development, leveraging multi-modal LLMs and classical statistics/ ML.
• 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.
• Provide analysis for launched solutions to quantify outcomes based on real-world results, identifying areas for improvement and opportunities for future development
• Be a cross-organization thought leader on both AI as a technology as well as on the next generation of challenges such as evaluations, inconsistent/ dirty labels.

Basic Qualifications

• Bachelor's/Master's degree in mathematics/statistics, computer science/engineering, or any other quantitative disciplines, with 8+ years of relevant experience working in industry or academia
• Deep hands-on experience across statistics and ML fundamentals, with a track record of applying them to production systems
• Strong critical thinking skills and ability to solve ambiguous problems, with proven experience in designing data science solutions to meet business problems
• 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:

• Production LLM/ agentic system experience
• Strong ability to model ambiguous business and operational problems at the appropriate level of abstraction, with a focus on delivering practical solutions
• Ability to think in systems that scale: pipelines, LLM-embedded workflows, Human In The Loop workflows, hybrid pipelines with context-specific agentic capabilities, etc.
• Advanced proficiency with machine learning frameworks and tools, including Python, TensorFlow, and PyTorch, and using them in conjunction with LLMs
• 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.

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/