EIT Digitalization Engineer(数字化)

At Jabil (NYSE: JBL), we are proud to be a trusted partner for the world's top brands, offering comprehensive engineering, supply chain, and manufacturing solutions. With 60 years of experience across industries and a vast network of over 100 sites worldwide, Jabil combines global reach with local expertise to deliver both scalable and customized solutions. Our commitment extends beyond business success as we strive to build sustainable processes that minimize environmental impact and foster vibrant and diverse communities around the globe.

职位概述

作为数字工程师，您将负责推动Jabil公司内部制造流程和运营数据的数字化转型。您将运用专业知识，将物理世界的信息转化为可操作的数字数据，以优化生产效率、提高质量并支持智能决策。

主要职责：

* 设计、开发并实施数据采集系统和传感器解决方案，将生产线、设备和环境数据数字化。

* 与IT、生产和工程团队紧密合作，识别数字化机会，并将其转化为可执行的技术方案。

* 负责数据的清洗、转换和集成，确保数据质量和一致性，为后续分析和应用奠定基础。

* 1. 了解生产现场：在工程师指导下熟悉电子制造流程，了解设备、测试和生产系统的数据，以及工程师、技术员处理异常的方式。

2. 提取与整理数据：使用SQL、Python等工具，从公司数据湖提取现有IoT、生产、测试和质量系统的数据，检查缺失、重复和时间不一致等问题，让数据准确、可用。

3. 发现与分析异常：分析不良率、测试通过率、设备停机和生产节拍等变化，定位异常发生的时间、产线、设备、工站和产品批次，为现场排查提供数据线索，并与工程师一起验证原因。

4. 让数据主动找人：制作清晰的看板和异常提醒，说明“哪里异常、影响什么、需要谁处理”; 依据产线、设备及值班分工，将异常推送给对应工程师或技术员，并跟踪接收、反馈、升级和关闭。

5. 跟进改善效果：与工程、生产、质量及IT团队合作，记录处理过程，对比改善前后的数据，确认问题是否解决，持续减少误报和重复异常。

6. 建立智能排障助手：整理经审核的作业指导书、设备资料和历史异常案例，协助开发可查询知识、引导排查步骤的AI智能体; 回答注明依据，不确定时转交工程师确认，不擅自修改设备参数或执行高风险操作。

7. 维护与推广应用：测试和维护数据分析脚本、看板及智能体，编写简单的使用说明，收集现场反馈，并遵守公司数据权限和信息安全要求。

任职资格：

* 本科或硕士应届毕业生，以下相关专业均可：

1. 优先专业：数据科学与大数据技术、计算机科学与技术、软件工程、人工智能、统计学或应用统计。

2. 相关工科专业：自动化、电子信息工程、物联网工程、智能制造工程、工业工程; 需具备数据分析和编程基础。

3. 能力基础：掌握SQL数据查询及Python基础，理解基本统计分析，愿意深入生产现场并与工程师、技术员沟通。

4. 加分经历（非必需）：制造数据分析、IoT、数据可视化、异常检测，或大模型知识库与智能体相关课程、毕业设计或项目。

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