Senior Manager – Customer Data Strategy & Advanced Analytics

Kimberly-Clark is a leading company dedicated to creating better care for a better world. They are seeking a Senior Manager for Customer Data Strategy & Advanced Analytics to drive and execute their customer data strategy, architecture, and advanced analytics initiatives, ensuring alignment with business priorities.

Responsibilities:

• Define and lead the MCX customer data strategy and roadmap that supports personalization, predictive analytics, and AI/ML enablement for Marketing and CX functions
• Architect scalable data infrastructure and pipelines in strategic partnership with data engineering and platform teams, enabling unified customer views and real-time analytics
• Own and deliver the unified customer view across platforms, developing and managing a 360 degree of the customer to drive intelligent targeting and interactions (CRM, marketing automation, service, commerce)
• Lead development, deployment, and optimization of predictive models and AI/ML solutions for segmentation, churn, personalization, and next-best-action
• Evaluate, prioritize, and manage AI/ML use cases across MCX, defining, developing and managing the AI/ML roadmap for the Marketing/CX function
• Single point of contact for translating MCX business needs into modeling requirements and ensure technical feasibility and scalability, working with data scientists and commercial analytics to develop, deploy and enhance
• Proactively identify and pursue opportunities to solve difficult and high-value problems using data, analytics, and AI/ML
• Guide and consult broad set of stakeholders on complex data science concepts, models, and findings into clear, compelling narratives tailored for executive audiences
• Accountable for business impact of advanced analytics including developing visualizations and presentations that highlight business impact, strategic relevance, and actionable insights
• Influence senior stakeholders by connecting technical outcomes to business priorities, enabling informed decision-making and investment alignment
• Activate product managers, CX and marketing teams, embedding models into campaigns, workflows, and customer experiences
• Drive operationalization of models across platforms (e.g., Salesforce, marketing automation, orchestration tools), ensuring performance, scalability, and ROI
• Accountable for model performance, retraining as needed, and optimization for ROI and business impact
• Lead pilot initiatives and long-term rollouts of model-based capabilities across CRM, analytics platforms, and downstream systems
• Ensure models are not only technically sound but operationally scalable, integrated into business workflows, and optimized for real-world performance
• Lead cross-functional teams to embed predictive capabilities into customer-facing and internal systems, driving measurable value and continuous improvement
• Own model efficacy by establishing monitoring and review processes to continuously evaluate and improve existing models, processes, and strategies to enhance performance and business impact
• Establish governance frameworks for ethical AI use, model lifecycle management, and data compliance
• Thought partner to legal, privacy, and IT teams to ensure ethical deployment of customer data and algorithms
• Influence senior stakeholders through strategic storytelling, connecting technical outcomes to business impact
• Lead cross-functional enablement efforts to build data literacy and adoption of analytics capabilities across teams
• Continuously evaluate emerging technologies and methodologies to enhance analytics maturity and enterprise readiness
• Act as a strategic advisor to CX, marketing, and product teams—translating complex analytics into actionable insights
• Build data literacy across the organization through storytelling, training, and enablement
• Establish business cases and outcome measurement for AI/ML initiatives
• Champion a culture of innovation and curiosity—exploring new tools, techniques, and approaches to data science and analytics

Requirements:

• 7-10 years in advanced analytics, data science, or related roles
• Strong expertise in statistical modeling and machine learning (Python, R, Spark, Snowpark)
• Proven experience designing and deploying enterprise-scale data and analytics solutions
• Experience operationalizing models in CRM, marketing automation, or personalization platforms
• Expertise with cloud data platforms (e.g., Snowflake, AWS, Azure)
• Experience with Generative AI and LLMs
• Proven ability to translate complex analytics into business impact
• Strong communication and leadership skills with a track record of driving measurable business outcomes
• Encourage experimentation and learning across the team to drive breakthrough thinking and scalable solutions
• Experience in B2B or B2B2B environments
• Familiarity with journey analytics, experience measurement, and orchestration platforms
• Experience with MLOps, model governance, and AI/ML lifecycle management