团队介绍&工作职责：
ATE (Analytics Technology and Engineering ) 是亚马逊物流供应链运营团队的一部分，其使命是为物流供应链运营创建核心分析技术能力和数据工程。我们致力于解决运营商从流程设计到执行和日常运营的端到端体验问题。团队由软件开发人员、科学家和工程师组成。我们优先考虑对多地区产生影响并在长期愿景中具有复制价值的项目。我们开发可扩展且标准化的解决方案，包括构建数据可见性、增加分析价值、提高操作员效率，并在可能的情况下消除手动工作。我们还集中数据架构，创建实时数据连接，并在各个地理位置上构建核心BI工程服务。

(高级) 运筹优化算法专家 将会在跨国项目中主导供应链物流系统的决策算法架构及持续迭代优化。结合运筹优化、机器学习等多领域算法，针对需求预测、产能规划、路径优化等业务需求建立数据及优化模型并推动算法落地实施。

岗位要求：
1.研究生及以上学历，运筹学、工业工程、应用数学等相关专业，博士优先；
2.熟练使用至少一门编程语言，如Python，Java， C++， R等；
3.具备扎实的运筹优化算法背景，包括线性规划、组合优化和启发式算法等，有大规模优化算法经验者优先；
4.有较强的学习能力和好奇心，具备良好的中英文沟通能力；
5.有常用机器学习算法经验、供应链与物流相关经验者优先。
Following English JD
Are you interested in applying your strong quantitative analysis and big data skills to world-changing problems? Are you interested in driving the development of methods, models and systems for strategy planning, transportation and fulfillment network? Are you interested to cooperate with Amazonians around the world? If so, then this is the job for you.

Our team, ATE(Analytics Technology and Engineering) is looking for an Applied Scientist to join our growing Science Team in Bangalore (India)/ Beijing(China). We are responsible for creating core analytics tech capabilities, quantative models, platforms development, and data engineering. We develop scalable analytics applications and research models to optimize operations processes. We standardize and optimize data sources and visualization efforts across geographies, build up, and maintain the online business intelligence services and data mart. You will work with other scientists, professional data engineers, business intelligence engineers, and product managers using rigorous quantitative approaches to ensure high quality data tech products for our customers around the world, including India, Australia, Brazil, Mexico, Singapore and Middle East.

Amazon is growing rapidly and because we are driven by faster delivery to customers, a more efficient supply chain network, and lower cost of operations, our main focus is in the development of strategic models and automation tools fed by our massive amounts of available data. You will be responsible for building these models/tools that improve the economics of Amazon’s worldwide fulfillment networks in different countries as Amazon increases the speed and decreases the cost to deliver products to customers. You will work on large-scale vehicle routing and scheduling problems under complex operational and physical constraints. You will also identify and evaluate opportunities to reduce variable costs by improving fulfillment center processes, transportation operations and scheduling, and the execution of operational plans. Finally, you will help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools.

Key job responsibilities

Design and develop complex mathematical, simulation and optimization models and apply them to define strategic and tactical needs and drive the appropriate business and technical solutions in the areas of vehicle routing, inventory management, network flow, supply chain optimization, demand planning.
Apply theories of mathematical optimization, including linear programming, combinatorial optimization, integer programming, dynamic programming, network flows and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software.
Translating business questions and concerns into specific analytical questions that can be answered with available data using Statistical and Machine Learning methods.
Prototype models by using modeling and programming languages with efficient data querying and modeling infrastructure.
Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions.
Collaborate with colleagues from multidisciplinary science, engineering and business backgrounds.
Manage your own process. Prioritize and execute on high impact projects, triage external requests, and ensure to deliver projects in time.

Basic qualifications

Ph.D. or Master's degree (with 4+ industrial experience) in Operations Research, Industrial Engineering, Applied Mathematics, Machine Learning, Statistics, Computer Science or a related quantitative field.
Hands-on experience in Python, Java, C++ or other similar languages.
Ability to convey mathematical results to non-science stakeholders.
Strength in clarifying and formalizing complex problems
Superior verbal and written communication and presentation skills in both Chinese and English, ability to convey rigorous mathematical concepts and considerations to non-experts.

Preferred qualifications

Experience with large-scale optimization and decomposition techniques such as column generation and meta-heuristics;
Practical experience applying ML to solve complex problems in an applied environment;
Significant peer-reviewed scientific contributions in premier journals and conferences;
Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis.

其他信息

行业要求：全部行业
所属部门：ATE