Responsibilities
- Design and execute complex analyses using statistical and computational methods to evaluate ecommerce performance, consumer behavior, and marketing effectiveness
- Apply advanced statistical techniques such as regression analysis, hypothesis testing, causal inference, and experimental design to evaluate business initiatives and product changes
- Develop predictive and descriptive models to estimate outcomes such as consumer lifetime value, purchase propensity, churn risk, and campaign performance
- Prototype and evaluate advanced analytical approaches, including machine learning methods and domain-specific models where appropriate
- Write highly optimized SQL queries to extract, transform, and analyze large-scale datasets across multiple relational databases and cloud data platforms
- Partner closely with data engineering teams to design and improve scalable data pipelines, data models, and data structures that support analytics and reporting needs
- Ensure data integrity, consistency, and accuracy across DTC data sources including ecommerce platforms, digital analytics, CRM, marketing systems, and operational data
- Contribute to improvements in data architecture, analytics workflows, and data governance practices that enable reliable and scalable analysis
- Design and build scalable dashboards and reporting solutions that enable stakeholders to monitor key DTC performance metrics and identify opportunities for growth
- Develop interactive visualizations and data products that communicate complex analytical results clearly and effectively
- Establish visualization standards and best practices that ensure clarity, consistency, and actionable storytelling across analytics outputs
- Deliver insights through compelling data storytelling that supports executive decision-making
- Define measurement frameworks and key performance indicators for ecommerce initiatives, digital marketing campaigns, and consumer engagement programs
- Lead experimentation initiatives, including A/B testing and experimental design, to evaluate product features, merchandising strategies, and marketing initiatives
- Analyze and interpret experimental results to provide clear recommendations and guide product and business strategy
- Develop standardized approaches for measuring funnel performance, customer journeys, and consumer lifecycle behavior
- Lead high-impact analytics projects that support Mattel’s Direct-to-Consumer ecommerce strategy and digital transformation
- Translate complex business questions into structured analytical approaches and technical solutions
- Mentor analysts on advanced analytical methods, coding standards, and best practices in analytics development
- Partner with product, marketing, merchandising, and technology teams to embed data-driven decision-making across the organization
Requirements
- Technically strong with a passion for solving complex problems
- Business-oriented mindset with ability to translate data into meaningful business impact
- Experience in applying advanced statistical techniques such as regression analysis, hypothesis testing, causal inference, and experimental design
- Proficiency in writing highly optimized SQL queries for large-scale datasets
- Experience working with cloud data platforms and relational databases
- Ability to design and build scalable dashboards and reporting solutions
- Experience in developing predictive and descriptive models (e.g., lifetime value, churn risk, purchase propensity)
- Proven ability to lead measurement strategy and experimentation (e.g., A/B testing)
- Strong data visualization and data storytelling skills
- Experience mentoring analysts and establishing best practices in analytics
- Ability to partner with cross-functional teams including ecommerce, digital marketing, product, merchandising, and technology
Nice to Have
- Experience prototyping and evaluating machine learning methods and domain-specific models
- Background in shaping evolving analytics strategies within a global DTC ecosystem
