Advanced Analytics Manager

About the role

As the Advanced Data Analytics Manager within the Market Digital Solutions Function, you will serve as the analytics expert supporting the business, digital, media, and communications functions by delivering customized insights and recommendations to drive performance. You will look across a broad range of data sources—including client, sales, media, digital platform, campaign, e-commerce, CRM, social, and relevant macroeconomic or market indicators—to understand marketing efficiency, business impact, client engagement, and external factors influencing performance. You will partner closely with division leadership, digital, media, and communication teams to support tailored analytics needs, KPI tracking, and strategic decision support, while also championing analytics best practices and upskilling division teams.

What you'll do

• Act as a strategic business partner, developing advanced custom analytics that translate business, media, digital, and market questions into impactful data insights and solutions.
• Collaborate with each division domain and cross-functional partners to address business questions using an expansive view of available data, without limiting analysis to client or sales datasets.
• Lead and execute analytics projects while providing ongoing support.
• Design and build interactive custom dashboards for real-time tracking of key performance indicators across luxury retail, clienteling, media, digital platforms, campaign performance, e-commerce, CRM, and other relevant business touchpoints.
• Develop semantic models for advanced KPI tracking, ensuring analytics reflect the nuances of luxury retail metrics and business logic.
• Integrate internal and external data sources where relevant, including media performance, owned and paid digital platforms, social signals, competitive context, consumer trends, and macroeconomic indicators.
• Analyze and explore large and diverse datasets to uncover patterns, trends, and performance drivers across client, sales, media, digital platform, campaign, social, e-commerce, CRM, market, and external data sources.
• Translate data into actionable insights by combining quantitative analysis, qualitative understanding, external context, and storytelling to support mid- to long-term business, marketing, and media 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.
• Design and execute A/B tests to move from hypotheses to validated actions.
• Apply causal inference techniques to identify true performance drivers.
• Assess the influence of external factors such as macroeconomic conditions, market trends, consumer sentiment, seasonality, competitor activity, and media environment on business and marketing performance.
• Quantify impact and prioritize initiatives by sizing opportunities, estimating ROI, assessing media and marketing efficiency, and guiding resource allocation.
• Track the adoption and business impact of delivered analytics solutions, ensuring dashboards and insights influence key luxury retail, media, marketing, and digital strategies.

Requirements

• 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, omni-channel performance metrics, media and marketing effectiveness measurement, and digital platform analytics.
• Ability to connect internal performance data with external indicators such as macroeconomic trends, consumer sentiment, competitive signals, and market context.
• 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.

Benefits

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