Lead Data Analyst, Customer Insights

As a Lead Data Analyst on the Customer Insights team, you will be a key influencer responsible for advancing the organization’s understanding of customers across brands, categories, and touchpoints. This role leads complex analytical initiatives that develop foundational customer insights, strengthen customer identity resolution, and enhance customer profiles used across the business. You will play a critical role in establishing the organization’s single source of truth for customer data and insights, translating large-scale customer datasets into meaningful insights that inform business decisions and improve customer experiences.

• This position is fully remote
• This role is an Individual Contributor position
  
  

A day in the life as a Lead Data Analyst, Customer Insights

• Lead the analysis of complex, high-impact customer analytics problems using advanced statistical and analytical methodologies
• Identify and interpret meaningful patterns, behavioral drivers, and anomalies in large customer datasets to uncover strategic insights across brands and categories
• Translate analytical findings into actionable insights and recommendations that inform business decisions
• Lead analytical initiatives that improve customer identity resolution across systems and channels
• Develop enriched customer profiles and customer-level datasets that support a consistent Customer 360 view
• Partner with data engineering teams to ensure the integrity and accessibility of customer data used for analytics
• Develop scalable analytical frameworks that establish the single source of truth for customer metrics and insights across the organization
• Design and maintain analytical data structures (feature sets, analytical tables, and transformation logic) that support consistent customer insights and reporting
• Design and implement A/B tests and experimental frameworks to evaluate customer behavior, engagement strategies, and business initiatives
• Apply advanced statistical techniques such as regression analysis, hypothesis testing, and causal inference to measure business impact
• Design and develop sophisticated dashboards and visualizations that clearly communicate customer insights to stakeholders
• Translate complex analytical outputs into clear, executive-ready narratives that influence strategic decision-making
• Establish best practices for analytical rigor, data visualization standards, and documentation
• Collaborate closely with data engineering, data science, and business teams to define analytical requirements and ensure high-quality data solutions
• Champion agile team practices (Scrum/Kanban) and contribute to continuous improvement in analytics workflows
• Stay current with emerging statistical methods, machine learning techniques, and data technologies
• Identify opportunities to improve analytical frameworks, customer data quality, and insight generation across the organization
  
  

What you’ll bring to the table…

• Expert-level SQL proficiency for complex data manipulation, transformation, and query optimization across large-scale datasets
• Advanced experience with data visualization tools (Tableau, Power BI, Looker) to develop interactive dashboards and analytical storytelling
• Strong expertise in statistical analysis and modeling techniques, including regression analysis, hypothesis testing, and causal inference
• Experience designing analytical frameworks for customer identity resolution, customer segmentation, or behavioral analytics
• Proficiency in Python or R for advanced data analysis, feature engineering, and predictive modeling
• Exceptional communication and collaboration skills with the ability to translate complex analytical findings into business insights
• Ability to influence cross-functional stakeholders and drive data-informed decision making
  
  

We’d love to hear from you if you have…

• 8 years of experience in a hands-on data analytics or customer analytics role.
• Bachelor’s degree in Data Science, Information Systems, Mathematics, Statistics, Business Analytics, or a related quantitative field (or equivalent practical experience)
• Proven experience leading complex analytical initiatives and delivering high-impact insights in an agile environment
• Strong experience working with large-scale customer datasets and analytical modeling frameworks
• Proficiency in Python or R for advanced data manipulation and modeling