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Generalist mid-level data analytics role, metro location, and known employer create high competition.
Core data skills are transferable but logistics and supply-chain domain knowledge raises industry specificity to medium.
Explicit 2–5 years requirement plus mandatory SQL/PowerBI/Tableau and logistics experience implies medium strictness.
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Own the availability, quality, and cleansing of global logistics data for the enterprise data lake.
Develop and maintain dashboards, reports, and analytical models to provide visibility into logistics performance metrics such as service, cost, compliance, and productivity.
Partner cross-functionally to prioritize and deliver analytics solutions within agreed timelines, ensuring alignment with global KPIs and data governance.
Bachelor’s degree in Supply Chain, Logistics, Industrial Engineering, Computer Science, Data/Analytics, Statistics, Business, or related field.
2–5 years of experience in logistics, transportation, supply chain, or data analytics.
Proficiency with data visualization tools (Power BI, Tableau) and data manipulation tools (SQL, Excel, Python).
Advanced English communication skills and ability to work in a global, cross-functional environment.
Experience translating end-to-end logistics business requirements into actionable analytics solutions in a global environment.
Strong technical skills to develop scalable data models and analytics with a solid understanding of logistics processes.
Familiarity with data governance, KPI standardization, data quality management, and enterprise data platforms (e.g., data lakes, Databricks, SAP, TMS, WMS).