China jobs in IT - Big Data

Data Strategy & Data Governance Leadership

· Define and maintain the APAC Data Strategy (architecture principles, governance model, standards, KPIs).

· Ensure data quality, privacy, and governance standards across all digital initiatives.

· Drive the alignment with ITD on data architecture, pipelines, integration, and security.

• Develop and maintain data models that align with business requirements and technical constraints.
• Collaborate with cross-functional teams to define data architecture strategies.
• Ensure data integrity, security, and compliance with industry standards.
• Lead data integration projects and manage data migration activities.

• You will work on various aspects of Big data analytics and development, Data Management, Governance and Information Architecture.
• Design and develop data solution architecture on scalability, good performance and flexibility throughout the entire data life cycle (ingestion, storage and consumption
• Define and prioritise product requirements, user stories, and acceptance criteria for data and analytics products and ensure what was agreed gets delivered

该岗位将负责公司数据平台的整体架构设计与搭建，涵盖数据湖、实时计算及查询优化，直接支持业务决策与创新。您将作为独立角色，承担主要数据项目，汇报至技术负责人。

This is an exciting opportunity for a Data Scientist to join a good business services company in Shanghai. The role involves working within the Data department to deliver data insights and solutions.

作为一名安全项目管理办公室（Security PMO），您将负责在快速消费品（FMCG）行业中协调和管理技术部门的安全相关项目。该职位需要具备优秀的项目管理技能以及对技术安全的深刻理解。

1、数据分析 - 结合业务痛点通过数据分析找到生意现象的本质原因，及推荐决策和期待的决策效果；

2、发展战略制定 -结合业务发展目标和现今痛点，定位并量化业务未来的发展主要动力，能制定未来短期中期和长期业务发展规划和战略，用数据指导业务发展战略；

工作职责：

负责大数据分析咨询业务的售前客户需求沟通和理解，熟悉企业经营方式，深刻理解企业营销、销售、产研、财务、售后等至少两个以上领域，基于公司的大数据/AI产品和服务为客户定制解决方案

Job Responsibilities:

• Data Analysis: Perform in-depth data analysis to identify trends and insights.
• Product Development: Drive the development of data-driven products and services.
• User Experience: Ensure data products meet the needs of end-users and enhance their experience.

工作职责：
1. 主要职责： 构建金融支付核心产品的关键业务指标体系，监控数据异常，分析潜在问题，及时识别业务风险，并提供专业建议以支持决策。
2. 数据驱动决策： 与业务团队合作，进行数据建模和迭代优化，运用AB测试等方法评估改进效果，推动业务部门的数据驱动决策。