Key Responsibilities
1. Business Partnership & Consulting
•Partner with business stakeholders to understand strategic priorities, operational challenges and decision-making processes.
•Translate ambiguous business questions into structured analytical approaches.
•Proactively identify opportunities where data can improve business performance.
•Facilitate data-driven decision making through structured problem solving and effective business storytelling.
2.BI & Dashboard Design
•Design intuitive, scalable dashboards that support operational, tactical and strategic decision making.
•Define meaningful KPIs, metrics and analytical frameworks across different business functions.
•Build reusable reporting assets and standardized performance monitoring frameworks.
•Continuously optimize dashboards based on user feedback and evolving business priorities.
•Ensure reporting focuses on actionable insights rather than data presentation.
3. Data Analytics & Insight Generation Conduct deep-dive across multiple business domains, including:
•Retail Performance
•CRM Analytics
•Merchandising & Product Performance
•E-commerce & Omnichannel Typical areas include:
•Sales performance tracking
•Store performance benchmarking
•Customer lifecycle analysis
•Product affinity & cross-selling
•Event performance reporting
•Conversion funnel analysis
•Business opportunity identification
4. Customer Data, Tagging & Information Layer Partner with business and tech teams to design scalable business taxonomies and tagging frameworks across enterprise data domains, including:
•Client (profile, lifecycle, preferences, engagement, value)
•Product (category, collection, style, attributes, occasion)
•Store (location, format, traffic, event, client mix)
•Client Advisor (expertise, portfolio, productivity, client interactions)
•Campaign & Marketing Activities
•Digital Touchpoints & Customer Journeys Responsibilities include:
•Translate business concepts into standardized data definitions, metadata and semantic models.
•Develop reusable business dimensions that improve reporting consistency.
•Contribute to enterprise KPI definitions and data governance standards.
•Improve analytical scalability through standardized business taxonomy and metadata management.
5. Data Analysis & Delivery
•Write efficient SQL/Python to extract, transform and analyze large datasets.
•Build reusable analytical datasets and reporting logic.
•Perform exploratory data analysis to uncover trends and business opportunities.
•Collaborate with tech team to improve data quality, availability and governance.
•Develop scalable data visualization and reporting solutions.
•Support automation of manual reporting and analytical processes.
6. Innovation Mindset
•Identify opportunities to automate reporting and analytical workflows.
•Explore AI-enabled analytics and next-generation Business Intelligence capabilities.
•Continuously improve analytical methodologies, visualization standards and insight delivery.
Key Requirements & Competencies
•5–8 years of experience in BI, Commercial Analytics or Data Analytics.
•Strong understanding of retail, luxury or consumer business.
•Ability to quickly understand business processes and translate them into analytical solutions.
•Strong stakeholder management, project management and consulting capabilities.
•Excellent communication and presentation skills in both Mandarin & English.
•Advanced SQL proficiency (required). Python or R experience is a plus.
•Strong experience with BI platforms (Power BI, Tableau or equivalent).
•Familiarity with dimensional data modeling and data warehousing concepts.
•Experience with cloud analytics platforms (Databricks, Dataiku, Snowflake, Alibaba DataWorks, etc.) is advantageous.
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Key Responsibilities
1. Business Partnership & Consulting
•Partner with business stakeholders to understand strategic priorities, operational challenges and decision-making processes.
•Translate ambiguous business questions into structured analytical approaches.
•Proactively identify opportunities where data can improve business performance.
•Facilitate data-driven decision making through structured problem solving and effective business storytelling.
2.BI & Dashboard Design
•Design intuitive, scalable dashboards that support operational, tactical and strategic decision making.
•Define meaningful KPIs, metrics and analytical frameworks across different business functions.
•Build reusable reporting assets and standardized performance monitoring frameworks.
•Continuously optimize dashboards based on user feedback and evolving business priorities.
•Ensure reporting focuses on actionable insights rather than data presentation.
3. Data Analytics & Insight Generation Conduct deep-dive across multiple business domains, including:
•Retail Performance
•CRM Analytics
•Merchandising & Product Performance
•E-commerce & Omnichannel Typical areas include:
•Sales performance tracking
•Store performance benchmarking
•Customer lifecycle analysis
•Product affinity & cross-selling
•Event performance reporting
•Conversion funnel analysis
•Business opportunity identification
4. Customer Data, Tagging & Information Layer Partner with business and tech teams to design scalable business taxonomies and tagging frameworks across enterprise data domains, including:
•Client (profile, lifecycle, preferences, engagement, value)
•Product (category, collection, style, attributes, occasion)
•Store (location, format, traffic, event, client mix)
•Client Advisor (expertise, portfolio, productivity, client interactions)
•Campaign & Marketing Activities
•Digital Touchpoints & Customer Journeys Responsibilities include:
•Translate business concepts into standardized data definitions, metadata and semantic models.
•Develop reusable business dimensions that improve reporting consistency.
•Contribute to enterprise KPI definitions and data governance standards.
•Improve analytical scalability through standardized business taxonomy and metadata management.
5. Data Analysis & Delivery
•Write efficient SQL/Python to extract, transform and analyze large datasets.
•Build reusable analytical datasets and reporting logic.
•Perform exploratory data analysis to uncover trends and business opportunities.
•Collaborate with tech team to improve data quality, availability and governance.
•Develop scalable data visualization and reporting solutions.
•Support automation of manual reporting and analytical processes.
6. Innovation Mindset
•Identify opportunities to automate reporting and analytical workflows.
•Explore AI-enabled analytics and next-generation Business Intelligence capabilities.
•Continuously improve analytical methodologies, visualization standards and insight delivery.
Key Requirements & Competencies
•5–8 years of experience in BI, Commercial Analytics or Data Analytics.
•Strong understanding of retail, luxury or consumer business.
•Ability to quickly understand business processes and translate them into analytical solutions.
•Strong stakeholder management, project management and consulting capabilities.
•Excellent communication and presentation skills in both Mandarin & English.
•Advanced SQL proficiency (required). Python or R experience is a plus.
•Strong experience with BI platforms (Power BI, Tableau or equivalent).
•Familiarity with dimensional data modeling and data warehousing concepts.
•Experience with cloud analytics platforms (Databricks, Dataiku, Snowflake, Alibaba DataWorks, etc.) is advantageous.
