信息技术职位 - 信息技术 - 大数据类别

• 参与大数据平台的整体架构设计，覆盖数据采集、存储、计算、分析及可视化全链路，确保系统高可用、高性能及可扩展性。
• 根据业务需求，选择阿里云（如MaxCompute、EMR、DataWorks）或 AWS（如Redshift、EMR、S3）等云平台技术，结合开源组件（如Hadoop、Spark、Flink、Kafka、HBase）实现技术方案。

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；

This role provides you with the opportunity to grow together with a young team in a good environment, and assist in completing the AI project landing for various BU groups in the Asia-Pacific region.

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.

• 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

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

Drive large-scale data architecture and optimize high-performance systems as a Big Data Engineer on Recommendation Architecture Team. Use your expertise in big data frameworks to build innovative, scalable solutions that enhance user experiences for millions globally.

工作职责：

利用数据分析和机器学习技术，优化商品【定价策略】和【大促活动】的数据策略

• 与营销、运营和供应链团队紧密合作，确保数据驱动的策略有效实施。
• 领导数据科学团队，推动数据分析项目，提升团队的专业技能和创新能力。

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。