Advanced Analytics Manager

As the Advanced Data Analytics Manager within the Market Digital Solutions Function, you will serve as the analytics expert supporting the business by delivering customized business insights and recommendations to drive performance. You will partner closely with division leadership to support tailored analytics needs, KPI tracking, and strategic decision support, while also championing analytics best practices and upskilling division teams.

Korean Language proficiency is essential, as the role requires effective communication with internal and external stakeholders.

Key Responsibilities:

Business Partnership

• Act as a strategic business partner, developing advanced custom analytics to translate business needs into impactful data insights and solutions.
• Collaborate with each division domain to address business questions with actionable analytical insights.

• Lead and execute analytics projects while providing ongoing support.
• Design and build interactive custom dashboards for real-time tracking of key luxury retail KPIs (e.g., clienteling effectiveness, product sell-through, boutique performance, high-value client segmentation).
• Develop semantic models for advanced KPI tracking, ensuring analytics reflect the nuances of luxury retail metrics and business logic.

• Analyze and explore large datasets to uncover patterns, trends, and performance drivers across domains, markets, or divisions.
• Translate data into actionable insights by combining quantitative analysis with qualitative understanding and storytelling to support mid- to long-term business planning.
• Validate insights through human feedback and stakeholder input.
• Leverage advanced models developed by the Data Activation and Intelligence Hub to support business operations and decision-making.
• Collaborate with Market teams to embed analytics into strategic and operational processes.
• Design and execute A/B tests to move from hypotheses to validated actions.
• Apply causal inference techniques to identify true performance drivers.
• Quantify impact and prioritize initiatives by sizing opportunities, estimating ROI, and guiding resource allocation.
• Support division and market leadership with clear recommendations for enhancing client experience, loyalty, and conversion across channels.

• Track the adoption and business impact of delivered analytics solutions, ensuring dashboards and insights influence key luxury retail strategies.
• Contribute to the development and documentation of KPI dictionaries and analytics standards tailored to luxury retail.

• Improved understanding of luxury client behaviors and preferences.
• Increased adoption and usage of analytics dashboards by retail and clienteling teams.
• Clear business impact in areas such as client retention, product performance, and boutique operations.
• Elevated analytics literacy and data-driven culture within luxury retail divisions.

• Presenting and storytelling complex analytics to non-technical luxury stakeholders.
• Creating business impact through exceptional client experiences and enabling data-driven luxury retail strategies.

• Excellent business acumen and communication skills.
• Passion for enabling data-driven insights and elevating a strong data culture.
• Bachelor’s or Master’s degree in Data Science, Analytics, Business, or a related field.
• 5+ years of analytics experience, preferably in retail or luxury sectors.
• Experience with luxury retail KPIs, customer journey analysis, and omni-channel performance metrics.

• Dashboarding Tools: Power BI, Tableau, or similar.
• SQL Proficiency: Strong hands-on experience in writing complex queries for data extraction, transformation, and analysis.
• Python & PySpark: Working knowledge for collaboration with data engineering and modeling teams, and handling large-scale data processing tasks.
• Databricks Navigation: Ability to work within Databricks notebooks, run queries, manage workflows, and collaborate across teams.
• Dashboard Development: Capable of building dashboards from scratch using tools like Power BI, Tableau, or Looker, focusing on usability and business relevance.
• Data Visualization: Skilled in designing clear, impactful visualizations that support storytelling and decision-making.
• Insight Translation: Ability to interpret raw data and transform it into actionable insights for business stakeholders.
• A/B Testing & Causal Inference: Familiarity with designing experiments and applying statistical methods to validate hypotheses and measure impact.