主分类：数据分析与数据科学
来源 JD 数据（旧分类保留，当前主分类见上方）
{
"schema_version": "via_ai_product_manager_jobs_v1",
"data_type": "ai_product_manager_jobs",
"job": {
"job_title": "Logistics Data Analyst",
"job_level": "未披露",AI生成
"work_category": "全职",AI生成
"department": "Keeta",
"location": "迪拜",
"work_mode": "未披露",AI生成
"job_category": "运营类"AI生成
},
"company": {
"company_name": "美团",
"company_industry": "科技零售 / 生活服务",
"company_size": "10000人以上",
"company_website": "meituan.com",
"company_description": "美团通过科技推动服务零售和商品零售的数字化，连接消费者与商户。"
},
"compensation": {
"salary_range": {
"min": "",
"max": "",
"currency": "未披露",
"cycle": "未披露"
},
"benefits": "未披露"
},
"requirements": {
"working_years": 2,
"degree": "Bachelor's degree in Information Systems",
"language": "3. Bilingual in English and Chinese — good command in both written and verbal communication is required for daily collaboration with global team.",AI生成
"visa_support": "未披露",
"responsibilities": "1. Fulfillment Analytics & Insight Generation\nAnalyze and derive insights from large, complex sets of data to monitor end-to-end logistics performance (capacity, efficiency, experience, rider behaviour, etc.). Independently identify business issues from data and translate them into insights that influence business decisions.\n\n\n2. Metric Framework Design & Reporting\nDesign and maintain performance monitoring frameworks. Create and enhance data visualizations and analytical tools to support business goals. Support logistics operation teams in setting targets and tracking performance. Own end-to-end data quality — from extraction and transformation to final analytical output.\n\n\n3. Cross-Functional Collaboration\nWork closely with various teams to align on operational priorities. Communicate data insights effectively to non-technical stakeholders and co-develop improvement initiatives. Drive the adoption of data-driven decision-making across teams to maintain operational excellence.\n\n\n4. Strategy Support & Execution Tracking\nParticipate in the formulation of capacity and experience strategies. Track execution outcomes, diagnose gaps, and recommend corrective actions based on data evidence.",
"requirements_text": "1. Bachelor's degree in Information Systems, Computer Science, Business Analytics, Statistics, Economics, or a related quantitative field.\n\n2. 2-3 years of experience with a strong focus on data analytics projects. Demonstrate from past experience ability to translate analysis into actionable business recommendations for non-technical stakeholders.\n\n3. Bilingual in English and Chinese — good command in both written and verbal communication is required for daily collaboration with global team.\n\n4. Growth mindset — you're a curious person who asks \"why\" before \"what,\". You are willing to learn new knowledge and adapt to a fast-paced environment.\n\n5.Experience integrating AI agents into daily work — you've used AI tools to automate repetitive tasks, accelerate analysis, or improve output quality.\n\nPreferred Qualifications:\nExperience in logistics, e-commerce, or on-demand platforms is a plus but not required — we value problem-solving ability over domain knowledge",
"skills": [AI生成
"团队协作",
"智能体开发"
],
"preferred_qualifications": "Preferred Qualifications:",
"job_highlights": "You'll work on real-life high-impact business problems with immediate feedback loops"
},
"contact": {
"recruiter_name": "未披露",
"contact_methods": [
{
"type": "apply_link",
"value": "https://zhaopin.meituan.com/web/position/detail?jobUnionId=4590467668&jobShareType=1"
}
]
},
"posting": {
"posting_id": "4590467668",
"post_date": "",
"hire_time": "未披露",
"update_date": "20260917",
"job_url": "https://zhaopin.meituan.com/web/position/detail?jobUnionId=4590467668&jobShareType=1"
},
"fulltext": "Logistics Data Analyst\nLogistics Data Analyst\n\n基础信息\n工作地点：迪拜\n部门：Keeta\n职位类别：运营类\n职位族群：产品运营\n更新时间：2026-06-26\n\n岗位职责\n1. Fulfillment Analytics & Insight Generation\nAnalyze and derive insights from large, complex sets of data to monitor end-to-end logistics performance (capacity, efficiency, experience, rider behaviour, etc.). Independently identify business issues from data and translate them into insights that influence business decisions.\n\n\n2. Metric Framework Design & Reporting\nDesign and maintain performance monitoring frameworks. Create and enhance data visualizations and analytical tools to support business goals. Support logistics operation teams in setting targets and tracking performance. Own end-to-end data quality — from extraction and transformation to final analytical output.\n\n\n3. Cross-Functional Collaboration\nWork closely with various teams to align on operational priorities. Communicate data insights effectively to non-technical stakeholders and co-develop improvement initiatives. Drive the adoption of data-driven decision-making across teams to maintain operational excellence.\n\n\n4. Strategy Support & Execution Tracking\nParticipate in the formulation of capacity and experience strategies. Track execution outcomes, diagnose gaps, and recommend corrective actions based on data evidence.\n\n岗位基本要求\n1. Bachelor's degree in Information Systems, Computer Science, Business Analytics, Statistics, Economics, or a related quantitative field.\n\n2. 2-3 years of experience with a strong focus on data analytics projects. Demonstrate from past experience ability to translate analysis into actionable business recommendations for non-technical stakeholders.\n\n3. Bilingual in English and Chinese — good command in both written and verbal communication is required for daily collaboration with global team.\n\n4. Growth mindset — you're a curious person who asks \"why\" before \"what,\". You are willing to learn new knowledge and adapt to a fast-paced environment.\n\n5.Experience integrating AI agents into daily work — you've used AI tools to automate repetitive tasks, accelerate analysis, or improve output quality.\n\nPreferred Qualifications:\nExperience in logistics, e-commerce, or on-demand platforms is a plus but not required — we value problem-solving ability over domain knowledge\n\n岗位亮点\nYou'll work on real-life high-impact business problems with immediate feedback loops\n1. Fulfillment Analytics & Insight Generation\nAnalyze and derive insights from large, complex sets of data to monitor end-to-end logistics performance (capacity, efficiency, experience, rider behaviour, etc.). Independently identify business issues from data and translate them into insights that influence business decisions.\n\n\n2. Metric Framework Design & Reporting\nDesign and maintain performance monitoring frameworks. Create and enhance data visualizations and analytical tools to support business goals. Support logistics operation teams in setting targets and tracking performance. Own end-to-end data quality — from extraction and transformation to final analytical output.\n\n\n3. Cross-Functional Collaboration\nWork closely with various teams to align on operational priorities. Communicate data insights effectively to non-technical stakeholders and co-develop improvement initiatives. Drive the adoption of data-driven decision-making across teams to maintain operational excellence.\n\n\n4. Strategy Support & Execution Tracking\nParticipate in the formulation of capacity and experience strategies. Track execution outcomes, diagnose gaps, and recommend corrective actions based on data evidence.\n1. Bachelor's degree in Information Systems, Computer Science, Business Analytics, Statistics, Economics, or a related quantitative field.\n\n2. 2-3 years of experience with a strong focus on data analytics projects. Demonstrate from past experience ability to translate analysis into actionable business recommendations for non-technical stakeholders.\n\n3. Bilingual in English and Chinese — good command in both written and verbal communication is required for daily collaboration with global team.\n\n4. Growth mindset — you're a curious person who asks \"why\" before \"what,\". You are willing to learn new knowledge and adapt to a fast-paced environment.\n\n5.Experience integrating AI agents into daily work — you've used AI tools to automate repetitive tasks, accelerate analysis, or improve output quality.\n\nPreferred Qualifications:\nExperience in logistics, e-commerce, or on-demand platforms is a plus but not required — we value problem-solving ability over domain knowledge",
"standard_classification": {
"std_category_code": "T017",
"std_aux_codes": [],
"std_category_status": null,
"std_taxonomy_version": "20261104"
}
}