亚马逊Applied Scientist Intern, International Technology, 2025 Beijing

职位：Applied scientist 应用科学家实习生 毕业时间：2025年10月 - 2026年9月之间毕业的应届毕业生 · 入职日期：2025年6月及之前 · 实习时间：保证一周实习4-5天全职实习，至少持续5个月 · 工作地点：北京朝阳区酒仙桥路恒通商务园区 · 校招信息请参考校园招聘申请手册： https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e 投递须知： 1 填写简历申请时，请把必填和非必填项都填写完整。提交简历之后就无法修改了哦！ 2 学校的英文全称请准确填写。 如果您正在攻读计算机视觉、生成式AI或多模态领域的博士或硕士研究生，而且对应用科学家的实习工作感兴趣。 如果您也喜爱深入研究棘手的技术问题并提出解决方案，用成功的产品显著地改善人们的生活。 那么，我们诚挚邀请您加入亚马逊的International Technology自动化营销团队改善亚马逊节假日促销的用户体验。我们的目标是帮助亚马逊的客户找到他们所需的产品，并发现他们感兴趣的新产品。 这会是一份收获满满的工作。您每天的工作都与全球数百万亚马逊客户的体验紧密相关。您将提出和探索LLM和CV领域的创新，例如如何精准控制最前沿的基座大语言模型和图像生成模型以满足自动化的需求。您将集成这些模型到工具链中生成个性化的促销广告图，通过标注数据、建模和客户反馈来完成闭环。您对模型的选择需要能够平衡业务指标和响应时间的需求。

A successful candidate will have deep experience in applied methods (statistical analysis, predictive modeling, classification, impact measurement), experience building reporting dashboards, and using those methods and tools to drive key business insights. These insights include but not limited to market growth opportunities and strategies, product opportunities, and advertiser behaviors. The role requires data science skills (i.e., a broad knowledge of existing data mining algorithms), strong business acumen, and knowledge on mobile ads market. You’ll work closely with a broad range of data professionals as well as business leaders. You’ll be working on projects where tools and methods are used to drive real-world business value. - Support DI, Product, Marketing, Partner Development with analytics for customer insights and product opportunity areas. - Quantify the impact of product, sales, and marketing initiatives on customer happiness, and future behavior. - Manage business analytic projects through all phases, including data quality, data modeling, algorithm/KPI development, statistical analysis, data visualization, and presentation of results and deliverables. - Monitor usage metrics, understanding business-based explanations for large scale trends, and patterns in customer lifecycle behavior.

A successful candidate will have deep experience in applied methods (statistical analysis, predictive modeling, classification, impact measurement), experience building reporting dashboards, and using those methods and tools to drive key business insights. These insights include but not limited to market growth opportunities and strategies, product opportunities, and advertiser behaviors. The role requires data science skills (i.e., a broad knowledge of existing data mining algorithms), strong business acumen, and knowledge on mobile ads market. You’ll work closely with a broad range of data professionals as well as business leaders. You’ll be working on projects where tools and methods are used to drive real-world business value. - Support DI, Product, Marketing, Partner Development with analytics for customer insights and product opportunity areas. - Quantify the impact of product, sales, and marketing initiatives on customer happiness, and future behavior. - Manage business analytic projects through all phases, including data quality, data modeling, algorithm/KPI development, statistical analysis, data visualization, and presentation of results and deliverables. - Monitor usage metrics, understanding business-based explanations for large scale trends, and patterns in customer lifecycle behavior.

• Bridges research and product development by applying cutting-edge techniques to solve real-world product challenges with limited guidance. • Collaborates across teams and contributes to technology transfer, patents, internal tools, and publications to drive business impact. • Maintains professional networks, supports recruitment efforts, and may assist in mentoring interns or junior team members. • Documents research processes, experiments, and findings to promote innovation and ensure reproducibility. • Applies advanced research strategies and gains deep expertise in areas like machine learning, NLP, computer vision, and statistical modeling to improve product quality. • Leverages data-driven approaches to optimize large-scale systems and ensure high performance; conducts AIGC research to enhance ad quality; analyzes offline and online performance to deliver scalable solutions that improve user and advertiser experiences.