[쿠팡로지스틱스서비스] Logistics Capacity Planning 데이터 관리/분석 담당자

📍 Job Overview

• Job Title: Logistics Capacity Planning 데이터 관리/분석 담당자
• Company: CLS (Coupang Logistics Services)
• Location: Seoul, South Korea
• Job Type: Full-time
• Category: Data Analysis & Management
• Date Posted: June 16, 2025
• Experience Level: Mid-Senior

🚀 Role Summary

The Logistics Capacity Planning team at CLS is responsible for predicting and managing the capacity of Coupang's delivery network to ensure efficient and reliable delivery of packages. The team works closely with various departments to provide data-driven insights and support, enabling informed decision-making and continuous improvement in delivery operations.

💻 Primary Responsibilities

1. Capacity Prediction and Data Analysis:

   • Predict daily delivery capacity based on historical data and current trends.
   • Analyze and interpret data to identify patterns, trends, and anomalies in delivery performance.
   • Develop and maintain data analysis models to improve prediction accuracy and identify areas for optimization.

2. Cross-Functional Collaboration:

   • Work closely with operations, planning, and delivery teams to understand their needs and provide tailored data solutions.
   • Collaborate with technology teams to develop and implement data-driven tools and dashboards for capacity management.
   • Participate in cross-functional meetings to present findings, answer questions, and drive data-informed decision-making.

3. Issue Resolution and Process Improvement:

   • Identify and address delivery bottlenecks and inefficiencies using data analysis.
   • Develop and implement data-driven strategies to improve delivery performance and reduce costs.
   • Monitor key performance indicators (KPIs) and continuously evaluate the effectiveness of capacity management processes.

4. Data Management and Quality Assurance:

   • Ensure data accuracy, completeness, and timeliness by validating sources and implementing data quality checks.
   • Develop and maintain data pipelines and ETL processes to automate data collection, transformation, and loading.
   • Collaborate with data engineering teams to optimize data infrastructure and improve data accessibility.

5. Stakeholder Communication:

   • Prepare and present regular reports and visualizations to senior management, highlighting key insights, trends, and recommendations.
   • Communicate complex data findings effectively to non-technical stakeholders, enabling informed decision-making.
   • Collaborate with external partners, such as delivery providers and technology vendors, to gather data and drive improvements.

🎓 Skills & Qualifications

Education: Bachelor's degree in Statistics, Mathematics, Computer Science, or a related field with a strong foundation in data analysis and statistics.

Experience: At least 4 years of experience in data analysis, data management, or a related role, with a proven track record in delivering data-driven insights and driving business impact.

Required Skills:

• Proficiency in SQL and experience with large datasets.
• Strong skills in data analysis, visualization, and reporting using tools such as Excel, Power BI, or Tableau.
• Experience with data processing and ETL tools, such as SQL Server Integration Services (SSIS) or Talend.
• Familiarity with statistical programming languages, such as R or Python, for advanced data analysis and modeling.
• Knowledge of logistics, supply chain, or operations management principles to understand and address delivery challenges.
• Excellent communication and presentation skills, with the ability to explain complex data findings to non-technical stakeholders.

Preferred Skills:

• Experience with cloud-based data platforms, such as AWS, Google Cloud, or Azure.
• Familiarity with big data technologies, such as Hadoop or Spark.
• Knowledge of logistics-specific software, such as transportation management systems (TMS) or warehouse management systems (WMS).
• Experience with Agile development methodologies and data-driven project management.

📊 Portfolio & Project Requirements

Portfolio Essentials:

• A portfolio showcasing your data analysis, visualization, and reporting skills, highlighting your ability to derive insights from complex datasets.
• Examples of data-driven projects that demonstrate your ability to identify trends, optimize processes, and drive business impact.
• Visualizations and reports that effectively communicate data insights to non-technical stakeholders.

Technical Documentation:

• Detailed documentation of your data analysis processes, including data sources, transformations, and modeling techniques.
• Code snippets or scripts that illustrate your data processing, analysis, and visualization techniques.
• Explanations of your data-driven decisions and the rationale behind your chosen approaches.

💰 Compensation & Benefits

Salary Range: Competitive salary based on experience and industry standards for data analysis roles in South Korea.

Benefits:

• Comprehensive health insurance coverage, including medical, dental, and vision care.
• Retirement benefits, including pension and retirement savings plans.
• Generous vacation and time-off policies, including annual leave, sick leave, and flexible work arrangements.
• Employee discounts on Coupang products and services, as well as employee stock purchase plans.
• Opportunities for professional development, including training, workshops, and conference attendance.

Working Hours: Standard full-time work hours, with flexibility for remote work and overtime as needed to support delivery operations.

💡 Team & Company Context

Industry: Logistics and supply chain management, focusing on efficient and reliable delivery of packages for e-commerce platforms.

Company Size: Medium to large, with a significant presence in South Korea and expanding operations in other Asian markets.

Founded: 2010, as a subsidiary of Coupang, focusing on providing innovative and efficient delivery solutions for the growing e-commerce market.

Team Structure:

• The Logistics Capacity Planning team is part of the broader CLS organization, working closely with operations, planning, and delivery teams to optimize delivery performance.
• The team consists of data analysts, data engineers, and data scientists, collaborating to develop and implement data-driven solutions for capacity management.
• The team structure fosters cross-functional collaboration and knowledge sharing, enabling continuous learning and improvement.

Development Methodology:

• The team follows Agile development methodologies, with a focus on iterative development, continuous improvement, and regular feedback.
• The team uses Scrum or Kanban boards to track progress, manage tasks, and ensure alignment with delivery goals and stakeholder expectations.
• The team works closely with technology teams to develop and deploy data-driven tools and dashboards, ensuring they meet user needs and drive business impact.

Company Website: Coupang Logistics Services

📈 Career & Growth Analysis

Role Level: Mid-Senior, with significant experience in data analysis, data management, or a related role, and a proven track record in driving data-driven insights and business impact.

Reporting Structure: The role reports directly to the Head of Logistics Capacity Planning, with a dotted-line reporting structure to relevant department heads, such as Operations and Planning.

Technical Impact: The role has a significant impact on delivery performance, capacity planning, and operational efficiency, directly contributing to the success of Coupang's delivery network and customer satisfaction.

Growth Opportunities:

• Career Progression: The role offers opportunities for career progression, including potential advancement to senior roles within the Logistics Capacity Planning team or related teams, such as Operations or Planning.
• Technical Skill Development: The role provides opportunities to develop and enhance data analysis, data management, and data visualization skills, as well as gain exposure to logistics and supply chain management principles.
• Leadership and Mentoring: As the team grows, there may be opportunities to mentor junior team members, fostering their professional development and contributing to the team's overall success.

🌐 Work Environment

Office Type: Modern, collaborative office spaces designed to facilitate cross-functional collaboration, knowledge sharing, and innovation.

Office Location: Seoul, South Korea, with convenient access to public transportation and nearby amenities.

Workspace Context:

• The workplace encourages open communication, active listening, and continuous learning, fostering a culture of collaboration and knowledge sharing.
• The team works in a dynamic, fast-paced environment, with a strong focus on data-driven decision-making and continuous improvement.
• The workplace offers opportunities for professional development, including training, workshops, and conference attendance, to support the growth and success of team members.

Work Schedule: Standard full-time work hours, with flexibility for remote work and overtime as needed to support delivery operations and meet customer demands.

📄 Application & Technical Interview Process

Interview Process:

1. Online Assessment: A short online assessment to evaluate your data analysis, problem-solving, and logical reasoning skills.
2. Phone Screening: A brief phone call to discuss your application, experience, and career goals.
3. On-site Interview: A series of on-site interviews with the hiring manager, team members, and relevant stakeholders, focusing on your technical skills, cultural fit, and problem-solving abilities.
4. Final Decision: A final decision based on your interview performance, cultural fit, and alignment with the team's needs and goals.

Portfolio Review Tips:

• Highlight your data analysis, visualization, and reporting skills, with a focus on projects that demonstrate your ability to derive insights from complex datasets.
• Showcase your ability to communicate data-driven insights effectively to non-technical stakeholders, enabling informed decision-making.
• Include examples of your problem-solving skills, with a focus on identifying trends, optimizing processes, and driving business impact.

Technical Challenge Preparation:

• Brush up on your SQL skills, focusing on data manipulation, aggregation, and subqueries.
• Familiarize yourself with data visualization tools, such as Excel, Power BI, or Tableau, and practice creating meaningful and engaging visualizations.
• Prepare for questions on data processing, ETL, and data quality, with a focus on real-world examples and practical applications.
• Review logistics, supply chain, and operations management principles, with a focus on delivery challenges and optimization strategies.

ATS Keywords: (Provided separately, as the list is comprehensive and organized by category)

🛠 Technology Stack & Web Infrastructure

Data Analysis & Management Tools:

• SQL Server Management Studio (SSMS)
• Microsoft SQL Server
• MySQL
• PostgreSQL
• Google BigQuery
• AWS Redshift
• Apache Spark
• Hadoop
• Python (Pandas, NumPy, Matplotlib, Seaborn)
• R (tidyverse, ggplot2, lattice)
• Excel (Power Query, Power Pivot)
• Power BI
• Tableau

Data Processing & ETL Tools:

• SQL Server Integration Services (SSIS)
• Talend
• Pentaho Data Integration (PDI)
• Apache Airflow
• AWS Glue
• Google Cloud Dataflow

Logistics & Supply Chain Management Software:

• Transportation Management System (TMS)
• Warehouse Management System (WMS)
• Warehouse Labor Management System (WLMS)
• Inventory Management System (IMS)
• Supply Chain Management (SCM) software

Collaboration & Communication Tools:

• Microsoft Teams
• Slack
• Google Workspace (Gmail, Google Meet, Google Docs)
• Zoom

Hardware & Infrastructure:

• Modern workstations with sufficient processing power and memory for data analysis and visualization tasks.
• High-speed internet connectivity, with reliable access to cloud-based data platforms and tools.
• Secure data storage and backup solutions, ensuring data integrity and confidentiality.

👥 Team Culture & Values

Data-Driven Decision-Making:

• The team values data-driven decision-making, with a strong focus on evidence-based insights and continuous improvement.
• Team members are encouraged to challenge assumptions, ask questions, and explore data-driven solutions to delivery challenges.

Collaboration and Knowledge Sharing:

• The team fosters a culture of collaboration and knowledge sharing, with a strong emphasis on open communication, active listening, and continuous learning.
• Team members are encouraged to share their expertise, insights, and best practices, contributing to the team's overall success.

Customer-Centric Mindset:

• The team is committed to understanding and addressing customer needs, with a focus on delivering exceptional customer experiences and driving business impact.
• Team members are encouraged to consider the customer perspective in their data analysis, visualization, and reporting efforts, ensuring their work supports customer-centric decision-making.

Innovation and Continuous Improvement:

• The team values innovation and continuous improvement, with a strong focus on driving operational efficiency, reducing costs, and enhancing customer satisfaction.
• Team members are encouraged to explore new data sources, tools, and techniques, and to challenge the status quo in their pursuit of data-driven insights and business impact.

⚡ Challenges & Growth Opportunities

Technical Challenges:

• Data Silos and Fragmentation: Addressing data silos and fragmentation across different departments, systems, and data sources, with a focus on data integration, consolidation, and standardization.
• Data Quality and Integrity: Ensuring data accuracy, completeness, and timeliness, with a focus on data validation, cleansing, and transformation techniques.
• Big Data Processing: Developing and implementing efficient big data processing techniques, with a focus on scalability, performance, and cost optimization.

Learning & Development Opportunities:

• Technical Skill Development: Expanding your data analysis, data management, and data visualization skills, with a focus on emerging technologies, tools, and best practices.
• Logistics and Supply Chain Management: Gaining a deeper understanding of logistics, supply chain, and operations management principles, with a focus on delivery challenges, optimization strategies, and industry trends.
• Leadership and Mentoring: Developing your leadership and mentoring skills, with a focus on fostering a culture of collaboration, knowledge sharing, and continuous learning within the team.

💡 Interview Preparation

Technical Questions:

• Data Analysis and Visualization: Questions focusing on your data analysis, visualization, and reporting skills, with a focus on real-world examples and practical applications.
• Data Processing and ETL: Questions focusing on your data processing, ETL, and data quality skills, with a focus on real-world examples and practical applications.
• Logistics and Supply Chain Management: Questions focusing on your understanding of logistics, supply chain, and operations management principles, with a focus on delivery challenges and optimization strategies.

Company & Culture Questions:

• Data-Driven Decision-Making: Questions focusing on your understanding of data-driven decision-making, with a focus on evidence-based insights and continuous improvement.
• Collaboration and Knowledge Sharing: Questions focusing on your ability to collaborate effectively with team members, with a focus on open communication, active listening, and continuous learning.
• Customer-Centric Mindset: Questions focusing on your ability to consider the customer perspective in your data analysis, visualization, and reporting efforts, ensuring your work supports customer-centric decision-making.

Portfolio Presentation Strategy:

• Data Analysis and Visualization: Highlight your data analysis, visualization, and reporting skills, with a focus on projects that demonstrate your ability to derive insights from complex datasets.
• Problem-Solving Skills: Showcase your problem-solving skills, with a focus on identifying trends, optimizing processes, and driving business impact.
• Customer-Centric Approach: Emphasize your ability to consider the customer perspective in your data analysis, visualization, and reporting efforts, ensuring your work supports customer-centric decision-making.

📌 Application Steps

To apply for this data analysis and management role at CLS, follow these steps:

1. Submit Your Application: Submit your application through the provided link, highlighting your relevant experience, skills, and career goals.
2. Prepare for the Online Assessment: Familiarize yourself with data analysis, problem-solving, and logical reasoning concepts, as well as brush up on your SQL skills.
3. Prepare for the Phone Screening: Review your application, experience, and career goals, and practice communicating your fit for the role and the team.
4. Prepare for the On-site Interview: Prepare examples of your data analysis, visualization, and reporting skills, with a focus on real-world examples and practical applications. Brush up on your logistics, supply chain, and operations management knowledge, and practice communicating your problem-solving skills and customer-centric approach.
5. Follow Up: After the interview, follow up with the hiring manager to express your interest in the role and address any remaining questions or concerns.

Important Notice: This enhanced job description includes AI-generated insights and web technology industry standards. All details should be verified directly with the hiring organization before making application decisions.