Ralph Lauren Data Science Manager

Ralph Lauren Corporation (NYSE:RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren's reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets. The Company's brand names, which include Ralph Lauren, Ralph Lauren Collection, Ralph Lauren Purple Label, Polo Ralph Lauren, Double RL, Lauren Ralph Lauren, Polo Ralph Lauren Children, Chaps, among others, constitute one of the world's most widely recognized families of consumer brands. At Ralph Lauren, we unite and inspire the communities within our company as well as those in which we serve by amplifying voices and perspectives to create a culture of belonging, ensuring inclusion, and fairness for all. We foster a culture of inclusion through: Talent, Education & Communication, Employee Groups and Celebration.

The CIX team is dedicated to leveraging consumer insights and predictive analytics to deliver personalized experiences at scale. The Data Science Manager - Marketing Mix Modeling (MMM), based in London as part of the Global CIX organization, will lead the end-to-end development, internalization, and long-term management of Ralph Lauren's global MMM program. Reporting to the Global Senior Director of Data Science, this role serves as the company's primary expert on MMM, overseeing external agency partnerships, ensuring a seamless transition to internal capabilities, and driving adoption and impact across all levels of the organization.

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• Serve as the global lead for Marketing Mix Modeling (MMM) at Ralph Lauren, driving strategic direction and execution.
  
• Scope, prioritize, and manage MMM initiatives to ensure alignment with key business objectives and delivery of actionable insights.
  
• Define and implement a long-term strategy to internalize MMM capabilities and embed them into core business decision-making processes.
  
• Oversee the external agency currently delivering MMM, ensuring high-quality outputs and strategic alignment.
  
• Monitor project timelines, deliverable quality, and adherence to business goals.
  
• Facilitate knowledge transfer from external partners to internal teams to support capability building.
  
• Lead the transition from outsourced MMM to a scalable, in-house capability.
  
• Develop processes, frameworks, and technical infrastructure to support ongoing MMM development and maintenance.
  
• Partner with data engineering and IT teams to integrate MMM into existing data pipelines and platforms.
  
• Establish and maintain Ralph Lauren's MMM knowledge base, including methodologies, model documentation, and use cases.
  
• Act as the central point of contact for MMM across the organization.
  
• Engage cross-functional stakeholders including Marketing, Finance, Strategy, and Executive Leadership to ensure MMM outputs inform decision-making.
  
• Conduct workshops and training sessions to drive understanding and adoption of MMM insights.
  
• Translate complex modeling results into clear, actionable recommendations tailored to various stakeholder levels.
  
• Track and report the impact of MMM insights on marketing ROI, budget allocation, and overall business performance.
  
• Continuously refine MMM methodologies to reflect market dynamics, evolving consumer behavior, and emerging data sources.
  
• Stay current with industry best practices, advanced econometric techniques, and AI/ML innovations relevant to MMM.
  

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• Demonstrated success in managing end-to-end Marketing Mix Modeling (MMM) projects, whether agency-side, client-side, or consulting capacity.
  
• Proven experience transitioning advanced analytics capabilities from external vendors to internal teams is highly desirable.
  
• Strong background in marketing analytics, econometrics, and business strategy-ideally within retail, fashion, luxury, FMCG, or technology sectors.
  
• Experience in data science, Statistics, Econometrics, Applied Mathematics, Economics, or a related quantitative field.
  
• Exceptional leadership and project management skills, with a track record of effectively engaging senior stakeholders.
  
• Ability to manage and influence vendor relationships while driving toward internal ownership and capability building.
  
• Excellent communication and data storytelling skills, with the ability to translate complex technical insights for both executive and technical audiences.
  
• Deep understanding of MMM methodologies, including regression techniques, Bayesian approaches, and machine learning applications.
  
• Proficiency in Python, R, SQL, and familiarity with MMM platforms or advanced econometric software.
  
• Strategic mindset with strong business acumen, capable of balancing analytical rigor with actionable business impact.
  
• Naturally curious and driven to innovate in the areas of marketing effectiveness and consumer analytics.