Data Science Director

Job Responsibilities

• Define and execute the Data Science strategy, aligning global roadmaps with local market priorities to drive revenue growth and operational efficiency.
• Act as a key thought partner to leadership, translating complex analytical findings into clear business recommendations and strategic actions.
• Drive the identification and deployment of AI-powered solutions across all LVA departments, including Operations, Merchandising, Finance, HR, Retail, and Client Development, with a focus on eliminating low-value, repetitive tasks and enabling forecasting, pattern recognition, and data-driven decision-making at scale.
• Ensure the AI agenda extends beyond any single function, delivering measurable productivity and quality gains for the entire organization.
• Maintain active alignment with LVMH Group / LV Central teams to ensure full visibility of Group/Maison-level AI initiatives, avoiding duplication of effort and leveraging centrally developed assets where available.
• Serve as the LVA relay for AI innovation: channel locally identified use cases to Central when relevant, and cascade Group/Maison roadmap priorities into the LVA context.

Innovation & Data Science Development

• Lead the application and scaling of advanced analytics, machine learning, and Generative AI solutions across customer interaction, media optimization, and automated communications.
• Lead the adaptation of global AI models to account for local cultural nuances, privacy regulations, and specific consumer behaviors.
• Scout and activate emerging use cases (e.g., Agentic AI), ensuring the Maison remains at the forefront of automated commerce and personalized content generation.
• Collaborate with IT and Client Development to build a unified data ecosystem, ensuring seamless model integration across all touchpoints.

Team Leadership & Functional Excellence

• Manage, mentor, and evolve a multidisciplinary team, fostering a culture of technical excellence and commercial acumen.
• Champion data literacy across the organization, fostering a culture where data is a strategic asset and AI empowers human talent.
• Prioritize and sequence the AI portfolio based on quantified business value, balancing quick wins that demonstrate tangible ROI with longer-term capability building.
• Ensure strong governance across data privacy, security, and lifecycle management practices, adhering to applicable regulations and internal standards.