Manage market intelligence and industry research, including collecting and analysing information for benchmarking, peer comparison, investor trends, and competitive landscape reviews.
Build scalable and reliable Extract, Transform and Load (ETL) processes for the ingestion and integration of large, structured and unstructured data from a variety of data sources, including systems that are on-premise and on cloud platforms.
Agentic Recommendation System: Explore the application of LLMs in data analytics, covering user behavior analysis, crowd segmentation, customer acquisition analysis, growth analytics and profitability analysis, and advance the implementation of the new paradigm of Agentic Data Analysis.
AI scenarios: Participate in the application of AI in client-side development and core business scenarios, helping build an AI-driven R&D and system capability framework. This includes, but is not limited to, improving development efficiency through AI, such as code generation, workflow-driven development, and business understanding; participating in the design and practice of AI Native / Agentic Commerce capabilities, including interaction models and capability abstractions for agents; exploring and contributing to cutting-edge AI payment capabilities and industry-standard protocols; and promoting intelligent capabilities across payment and financial flows, such as decision intelligence, recommendation intelligence, and experience intelligence, to continuously improve engineering efficiency and business outcomes.
Explore the application and implementation of cutting-edge research such as large language models, graph neural networks, and multimodal techniques in financial risk scenarios.
AI scenarios: Participate in the application of AI in front-end development and core business scenarios, helping build an AI-driven R&D and system capability framework. This includes, but is not limited to, improving development efficiency through AI, such as code generation, workflow-driven development, and business understanding; participating in the design and practice of AI Native / Agentic Commerce capabilities, including interaction models and capability abstractions for agents; exploring and contributing to cutting-edge AI payment capabilities and industry-standard protocols; and promoting intelligent capabilities across payment and financial flows, such as decision intelligence, recommendation intelligence, and experience intelligence, to continuously improve engineering efficiency and business outcomes.