Senior Data Analyst

About this task

岗位职责：
1. 基于仓储运营绩效数据，在Tableau中搭建自动化仪表板，监控关键KPI。
2. 负责数据提取、清洗、存储及可视化机制的技术开发与优化，确保数据链路稳定可靠。
3. 建立绩效指标相关的文档与培训文件库，确保团队可便捷访问指标口径、报表逻辑及操作指南。
4. 利用Python、SQL或ETL工具创建新数据源，扩展分析维度。
5. 每周/每月输出业务复盘报告，涵盖业务流程优化指标、劳动力绩效分析、产能规划建议等内容。
6. 针对异常波动发起深度分析，定位根因并提出改进方案。
7. 负责仓储相关指标、报表、分析模型及仪表板的全生命周期管理，主动识别运营中的分析盲点，推动数据采集与逻辑补全。
8. 在业务关键期（如大促、库存盘点、系统切换）严格按时交付分析结果，支持快速决策。

任职要求：
1. 本科及以上学历，工程、物理、数学、统计学、计算机等相关专业。
2. 5年及以上物流或供应链行业数据分析工作经验，其中至少3年与仓储/配送相关。
3. 精通Python及SQL，具备预测算法开发经验，熟练使用Tableau，能独立搭建复杂仪表板及数据故事。
4. 熟悉仓储核心指标，能独立完成产能建模、劳动力需求测算或预测模型落地。
5. 英语可作为工作语言。
6. 结果导向，能适应跨文化和跨时区协作；抗压能力强，接受业务高峰期的分析与报告任务。

工作地点：驻巴西。工作语言：英语。驻外时长：2年。

Job responsibilities:
1. Build automated dashboards in Tableau based on warehousing operations performance data to monitor key KPIs.
2. Be responsible for the technical development and optimization of data extraction, cleaning, storage and visualization mechanisms to ensure a stable and reliable data pipeline.
3. Establish documentation and training file libraries related to performance metrics, ensuring the team can easily access metric definitions, report logic and operation guides.
4. Use Python, SQL or ETL tools to create new data sources and expand analysis dimensions.
5. Produce weekly/monthly business review reports covering business process optimization metrics, labor performance analysis, capacity planning recommendations and related topics.
6. Conduct in-depth analysis of abnormal fluctuations, identify root causes and propose improvement plans.
7. Manage the full lifecycle of warehouse-related metrics, reports, analytical models and dashboards; proactively identify analytical blind spots in operations and drive data collection and logic completion.
8. During critical business periods such as major promotions, inventory counts and system transitions, deliver analysis results strictly on time to support rapid decision-making.

Requirements:
1. Bachelor's degree or above in engineering, physics, mathematics, statistics, computer science or related fields.
2. At least 5 years of data analysis experience in the logistics or supply chain industry, including at least 3 years related to warehousing/distribution.
3. Proficient in Python and SQL, with experience in predictive algorithm development; skilled in Tableau and able to independently build complex dashboards and data stories.
4. Familiar with core warehousing metrics, and able to independently complete capacity modeling, labor demand estimation or predictive model implementation.
5. English can be used as a working language.
6. Results-oriented, able to adapt to cross-cultural and cross-time-zone collaboration; strong ability to work under pressure and able to handle analysis and reporting tasks during business peak periods.

Work location: stationed in Brazil. Working language: English. Overseas assignment duration: 2 years.