Logistics Analytics Specialist
Full-time
Shopee
About The Team As a Logistics Analytics Specialist, you will sit at the intersection of heavy data engineering, day-to-day e-commerce logistics operations, and data automation (including use of AI LLM and agentic models). You won't just build dashboards or run reports; you will own the end-to-end data pipelines that optimize our supply chain, from when the buyer searches for a product listed on the Shopee platform, to the moment the buyer receives the products. Job Description Logistics Insights & Performance Analytics
- Deep-dive into logistics data to track and optimize critical KPIs.
- Run ad-hoc analyses on delivery performance, bottle necks, and sudden spikes.
- Provide insights and recommendations to management based on data analysis.
- Design, optimize, and maintain automated ETL (Extract, Transform, Load) data pipelines specifically for high-volume supply chain data
- Build, update, and manage BI dashboards to give operations managers real-time visibility on metrics and KPIs.
- Main PIC for Logistics team to test, refine, and roll out internal LLM models, and automation agents.
- Actively utilize generative AI tools and basic automation to speed up data cleaning, querying, and report generation as well as implementation of process automation for teams’ manual processes.
- Provide feedback to BI team to ensure the AI agents they build accurately understand e-commerce logistics nuances.
- Bachelor’s degree in a quantitative field (e.g., Economics, Business, Statistics, Mathematics, Computer Science, Engineering) or equivalent practical experience.
- At least 2 years in analytics / BI / Business Analysis / Ops Analytics.
- Advanced Excel / Google Sheets skills.
- Strong SQL and data wrangling skills; ability to work independently with large datasets.
- Hands-on experience interacting with LLM APIs and basic knowledge of framework paradigms for internal agent architectures.
- A proactive, problem-solving mindset that thrives on ambiguity and rapid e-commerce campaign cycles.
- Solid analytical fundamentals: descriptive analysis, driver/root-cause analysis, cohort/funnel style thinking as applicable.
- Practical BI/reporting skills (e.g., dashboards, scorecards, automated reporting) and comfort maintaining existing assets.
- Exceptional communication skills—ability to translate dense technical metrics into simple, operational strategies.
Vacancy posted 16 hours ago
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