In this role, you will own the full data lifecycle — from pipeline architecture and data modeling through to statistical analysis and AI-driven insight generation. You will work closely with cross-functional teams spanning marketing, business operations, partner management, and engineering.
Early on, you will focus on standing up data infrastructure: building ingestion pipelines, automating dashboards, identifying data gaps, and ensuring data governance and compliance. As the foundation matures, you will shift toward data science — designing experiments, generating customer insights, and applying machine learning to optimize initiatives for sales growth.
You will also contribute to the development of data platforms that enable seamless collaboration with external and internal partners, and help scale analytics capabilities across the organization.
Minimum Qualifications
5+ years of relevant work experience in data engineering, data science, or a combined role, with hands-on depth across both disciplines
Proficiency in Python and SQL, with experience building and maintaining ETL/ELT pipelines, data models, and automated dashboards
Experience with marketing data science methods including experimental and testing design, regression analysis, and causal inference
Solid understanding of data governance, compliance, and access control principles
Strong problem-structuring skills, with the ability to work through ambiguity and define clear analytical approaches
Excellent communication and stakeholder management skills, with the ability to present to non-technical business audiences
Fluent verbal and written communication skills in both Korean and English
Preferred Qualifications
Experience with cloud data platforms (e.g., Snowflake)
Proficiency in machine learning methods applied to customer analytics, business optimization, or forecasting
Experience building data-sharing platforms or partner data integration workflows
Background in business analytics (e.g., attribution, funnel analysis, customer lifetime value, marketing mix modeling)
Exposure to digital advertising, marketplaces, e-commerce, media, or consumer technology business related analysis
Experience identifying repeatable business problems and converting them into scalable tools or automated workflows
Master’s or PhD in Computer Science, Statistics, Data Science, Economics, Operations Research, Engineering, or a related quantitative field with 5+ years of relevant experience