Director, Applied Data Science Data Science

Coupang
Taipei, TaiwanPosted 26 March 2026

Job Description

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. 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. Role Overview: As a Director, Analytics Data Science (Growth Marketing) , you will be responsible for leveraging data points to drive actionable insight and analysis. Work closely with Growth Marketing teams to deliver impact across the customer lifecycle. Come join us and help create a WOW experience for our customers. This is a great opportunity to be part of a diverse, growing, and dynamic team with upward growth potential. You will be part of an early-stage international expansion team where you will get a broad end-to-end view of aggressive expansion of an e-commerce business. For this reason, we are looking for a hands-on Director of Analytics Data Science who is comfortable working in a fast-paced environment and delivering results with grit. What You Will Do: Understand business goals and formulate them as technical problems that can be solved through Analytics, Data Science, and BI reporting. Work as a player-coach to drive value for several Growth Marketing channels, including Paid, CRM, On-Site Merchandising, and Product. Partner closely with Growth Marketing teams to provide actionable insight and recommendations. Regularly present findings to leadership and stakeholders. Build and maintain automated dashboards and data pipelines. Create and automate new datasets for syndicated reporting Work with omnichannel attribution measurement frameworks that drive incrementality and customer growth. Design and conduct experiments and A/B tests to measure marketing initiatives. Apply statistical rigor and causal inference to measure incrementality Build and maintain ML models that help drive decision making and optimization. Partner closely with Data Science and Growth Marketing teams to deploy ML solutions that optimize data feeds and audience targeting. Spearhead technical excellence in Analytics, Data Science, and BI reporting. Establish processes that raise the bar for excellence, effectiveness, and efficiency, including documentation, data quality, code hygiene, and integration with AI tools. Essential Qualifications Bachelor’s/Masters/PHD in math, statistics, computer engineering or any other quantitative disciplines, with 10+ years of relevant experience Minimum 5+ years managing Analytics and/or Data Science teams focused on Growth Marketing. Experience managing and mentoring a team of Analysts and Data Scientists. Expert and hands-on experience using Python, SQL, R and visualization tools. Experience data mining a variety of large datasets, including weblogs, clickstream, and customer data. Strong experience building automated reporting and dashboards. Working knowledge of using orchestration tools to automate ETLs and data pipelines. Experience with big data tools like Hadoop, Spark, and Presto Expert in experimentation and A/B testing. Strong knowledge of math, statistics, and causal inference techniques to measure ... (truncated, view full listing at source)
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