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공고 내용
Company Introduction
Role Overview
The Catalog team plays a pivotal role in delivering a seamless eCommerce experience, as it directly shapes how customers discover and purchase products online.
This role combines senior-level business analysis with a strong foundation in statistical methodology and data analytical expertise. The position focuses on turning vague business questions into measurable analytical problems, conducting hypothesis-driven deep dives, and delivering actionable insights to support business decision-making. The ideal candidate is comfortable performing advanced analytics (such as EDA, cohort analysis, and experimental design) while having practical familiarity with data systems and ETL pipelines to support their analytical workflows.
What You Will Do
Advanced Analytics Problem Solving
-Turn vague business questions into structured, measurable analytical problems using hypothesis-driven analysis, root cause analysis, and systems thinking.
-Conduct exploratory data analysis (EDA), time series analysis, segmentation/clustering, and cohort analysis to uncover business opportunities and solve complex catalog challenges.
-Design and execute experiments, applying statistical inference, hypothesis testing, and sampling methodologies to validate business impacts.
-Utilize Python/R and advanced analytics techniques (including feature engineering) to extract actionable insights from large-scale data.
Data Engineering Infrastructure Support
-Design, build, and maintain scalable ETL/ELT pipelines, data lake architecture, and API integration using Python and modern data warehouses (Snowflake/BigQuery).
-Implement data quality checks, maintain core data tables/lineage, and optimize SQL queries to ensure backend reliability, performance, and self-serve analytics enablement.
Business Partnership Solution Design
-Collaborate closely with catalog and cross-functional business teams to translate requirements into data models, analytical frameworks, and dashboards.
-Partner with external teams on special projects to investigate, diagnose, and mitigate business challenges through data.
Continuous Improvement
-Stay current with evolving data technologies, tools, and industry best practices.
-Proactively identify opportunities to enhance data infrastructure and analytical capabilities.
Basic Qualifications
- Strong business analysis and problem-solving skills with the ability to turn vague business questions into measurable analytical problems using hypothesis-driven analysis and systems thinking.
- Experience in advanced data analysis techniques using Python or R (EDA, feature engineering, time series analysis, cohort analysis, and segmentation/clustering).
- Solid background in statistical methods, including experimental design, hypothesis testing, statistical inference, and sampling methodologies.
- Advanced SQL skills with experience optimizing queries in modern data warehouses (e.g., Snowflake, BigQuery).
- Proven experience or familiar understanding in data engineering (ETL/ELT pipelines, data modeling, API integration, and pipeline optimization).
- Experience with data quality frameworks, monitoring tools, and ability to communicate technical/statistical concepts clearly to non-technical stakeholders.
Recruitment Process and Others
Recruitment Process
- Application Review - Job Fit Interview - Focus Interview - Offer
Details to Consider
- This job posting may be closed prior to the stated end date for application if all openings are filled.
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