Data and AI Product Analyst.
Responsibilities:
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Data Product Planning and Design:
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Deeply understand business data needs (e.g., operations, growth, monetization).
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Responsible for planning and designing data products (including dashboards, analytics platforms, data API services, etc.).
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Independently create product requirement documents (PRD), data dictionaries, and product prototypes, clearly defining product boundaries and core functionalities.
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Full-Process Project Management:
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Coordinate with data development, engineering, testing, and business teams to drive data products from requirement review, development, and testing to deployment and maintenance.
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Ensure project timelines, quality, and alignment with business requirements.
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Data Product Iteration and Optimization:
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Establish feedback mechanisms to collect user opinions and operational issues.
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Use key product metrics (e.g., usage rate, query efficiency, problem resolution rate) to formulate iteration plans and drive optimization.
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Data Requirement Discovery and Implementation:
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Collaborate with business teams to identify potential data needs and translate ambiguous requirements into actionable product solutions.
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Work with the data development team to clarify data sources and calculation logic, ensuring data accuracy and product usability.
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Support for Data Asset Management:
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Participate in data asset organization and management.
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Assist in building data standards and guidelines.
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Promote efficient reuse of data assets in products to enhance data value realization.
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Competitor and Trend Analysis:
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Monitor industry data product trends.
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Conduct competitor analysis of features, architecture, and user experience.
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Propose product optimization and innovation directions based on business realities.
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Requirements:
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Education and Experience:
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Bachelor’s degree or above, with at least 3 years of relevant data product experience.
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Experience in the internet industry (e.g., e-commerce, community platforms, social media, entertainment) is preferred.
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Familiar with data warehouse and data lake architectures and basic principles of common data processing technologies (Hadoop, Spark, Flink, etc.).
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Core Product Skills:
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Experience in full-process data product design and implementation, able to independently manage the end-to-end product lifecycle.
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Proficient in prototyping tools (Axure, Figma) and basic data tools (SQL, Python) for simple data queries and analysis.
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Data and Business Understanding:
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Strong data sensitivity; can accurately understand the connection between business logic and data needs.
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Able to solve real business problems through data product design.
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Familiar with common data analysis methods (e.g., funnel analysis, user segmentation, attribution analysis).
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Communication and Collaboration Skills:
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Excellent cross-team communication and coordination skills.
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Able to clearly interface with business, data, and engineering teams, efficiently convey requirements and technical boundaries, and drive consensus.
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Logical Thinking and Execution Ability:
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Strong analytical and logical thinking skills; able to extract core goals from complex requirements.
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High execution efficiency, able to handle multiple concurrent tasks and ensure timely project delivery.
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Laura Masterson
Recruitment Consultant
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