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. ------------------------------------------- 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.

Bi & Analytics Manager/Bi & Analytics Manager