
Manager II, Data Analysis
- 서울시
- 정규직
- 풀타임
- Lead & Mentor: Manage and develop a small team of business and data analysts, fostering their technical and professional growth. Guide the team in tackling complex analytical problems and delivering high-impact insights.
- Individual Contribution & Deep Dives: Serve as a hands-on technical leader by personally executing deep-dive analyses. Move seamlessly from a high-level problem statement to a detailed solution, demonstrating a strong ability to work through ambiguity and complex data-wrangling challenges.
- Stakeholder Management & Prioritization: Collaborate directly with product managers, operations leaders, and engineering teams to understand business needs, define the analytics roadmap, and manage project prioritization in an agile workflow.
- Drive Simplification: Champion and implement best practices for creating simple, effective, and sustainable analytics solutions. Focus on minimizing technical debt in reports, dashboards, and data models, and proactively identify opportunities to consolidate metrics and dashboards where synergies exist to ensure long-term scalability.
- Develop Visualizations & Reporting: Oversee the development of and contribute to building insightful, automated, and user-friendly dashboards and reports using BI tools (e.g., Tableau, Power BI) to track key performance indicators and empower stakeholders with self-service analytics.
- Enhance Data Strategy: Define critical business metrics, establish processes for monitoring performance against goals, and identify opportunities to improve data quality and analytics infrastructure.
- Bachelor's or Master's degree in a quantitative field (e.g., Business Analytics, Statistics, Engineering, Computer Science, Economics, or a related discipline).
- 5+ years of experience in data analysis, business intelligence, or a related field, with at least 1-2 years of experience managing a team or acting as a formal project/team lead.
- Proven ability to act as both an individual contributor and a team manager.
- Expert-level proficiency in writing and optimizing complex SQL queries on large-scale datasets.
- Strong, hands-on experience with data visualization tools like Tableau, Power BI, Looker, or similar.
- Demonstrated ability to tackle ambiguous problems, perform "dive deep" investigations to find root causes, and deliver solutions even when data definitions are not straightforward.
- Excellent written and spoken communication skills in English.
- Proven ability to discuss project priorities and trade-offs effectively with senior stakeholders.
- Experience working in an agile development environment.
- Proficiency in Python (particularly Pandas, NumPy) for data manipulation and analysis.
- Experience in Supply Chain Management, Logistics, E-commerce, or a related operations-focused industry.
- Experience with statistical analysis techniques (e.g., hypothesis testing, regression).
- Ability to use large-scale data ecosystems and tools like PySpark.