大数据图谱工程师 (R-18356) at Dun & Bradstreet, Inc - Canada

Shanghai, Shanghai, China -

Full Time

Start Date

Immediate

Expiry Date

28 Dec, 25

Salary

0.0

Posted On

29 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Java, Python, Scala, Graph Database, Hadoop, Spark, Flink, Kafka, ElasticSearch, Graph Computing, Entity Relationship Extraction, Knowledge Fusion, System Design, Problem Analysis, Team Collaboration, English Proficiency

Industry

Information Services

Description

为什么选择在邓白氏工作邓白氏解析数据的力量，创造更美好的未来。每一天，我们都在探索新的方式以持续推动追求卓越的文化，加速创新和成长。全球6000多名员工都对自己的工作充满热情。我们致力于协助客户将未知转化为信心，将风险转化为机遇，将潜力转化为增长。我们始终欢迎敢于梦想且多元化的人才。快来加入我们吧！【岗位职责】负责构建和优化企业级知识图谱系统，设计图谱架构与数据模型；参与大规模异构数据的采集、清洗、融合与图谱构建，提升数据质量与图谱覆盖率；设计并实现图数据库的查询优化、图计算算法及图谱服务接口；与产品、数据科学、业务团队紧密合作，推动图谱在推荐、搜索、风控、智能问答等场景中的落地应用；跟踪图谱技术发展趋势，持续推动技术创新与平台能力升级。【任职要求】计算机、软件工程、人工智能等相关专业硕士及以上学历，具备扎实的编程能力（Java/Python/Scala）； 3年以上大数据或知识图谱相关工作经验，熟悉图数据库（如 Neo4j、JanusGraph、Nebula等）及其应用；熟悉主流大数据技术栈，如 Hadoop、Spark、Flink、Kafka、ElasticSearch 等；熟悉图计算、图嵌入、实体关系抽取、知识融合等核心技术；具备良好的系统设计能力、问题分析能力和团队协作能力；英语读写能力良好，能熟练进行书面交流。【加分项】有开源项目贡献者优先；熟悉LLM与图谱结合的应用场景者优先；有大型图谱项目落地经验者优先，有AI/NLP背景者优先。 \n \n 申请指南如您要申请该职位，请点击“申请该职位”按钮。屏幕将跳转至新的页面，显示以下字段：简历、全名、电子邮箱、电话号码和当前供职公司。您可以选择提供关联至您的Linkedin、GitHub、portfolio、Twitter或其它网站的链接。您也可以在“附加信息”中添加推荐信、更多个人信息或您对该职位的意向。最后，请点击“提交申请”按钮以完成申请。我们期待您的申请！ All Dun & Bradstreet job postings can be found at https://jobs.lever.co/dnb. Official communication from Dun & Bradstreet will come from an email address ending in @dnb.com. Notice to Applicants: Please be advised that this job posting page is hosted and powered by Lever. Your use of this page is subject to Lever's Privacy Notice and Cookie Policy, which governs the processing of visitor data on this platform.

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Responsibilities

Responsible for building and optimizing enterprise-level knowledge graph systems, designing graph architecture and data models. Collaborate closely with product, data science, and business teams to drive the application of graphs in various scenarios such as recommendation, search, risk control, and intelligent Q&A.