Live opening · Posted 2 days ago

Manager Data Analytics

Mattel · El Segundo, CALIFORNIA, United States
Smartrecruiters No Full-time
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At a glance

The key details from the original listing.

Posted 2 days ago
CompanyMattel
LocationEl Segundo, CALIFORNIA, United States
Job typeFull-time
Work modeNo
SkillsPython, Tableau
SourceSmartrecruiters
ListedPosted 2 days ago

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About the role

Description supplied by the original job listing.

The Opportunity:
The Manager, Data Analytics plays a critical role within Mattel’s DTC Consumer Data & Analytics team, helping unlock the value of consumer and ecommerce data to drive business growth. This role sits at the intersection of analytics, technology, and business strategy—partnering with stakeholders across ecommerce, digital marketing, product, merchandising, and technology to transform data into actionable insights.
As a leader on the analytics team, you will drive complex analytical initiatives, guide measurement strategy, and develop scalable reporting and analytical solutions that help the organization understand consumer behavior, optimize performance, and identify opportunities for growth. You will also mentor analysts on the team, establish best practices in analytics and experimentation, and help shape the evolving analytics strategy supporting Mattel’s global DTC ecosystem.
The ideal candidate is both technically strong and business-oriented, with a passion for solving complex problems, mentoring others, and translating data into meaningful business impact.
What Your Impact Will Be:
Advanced Analytics & Modeling
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
Data Engineering & Data Architecture Collaboration
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
Data Visualization & Analytics Products
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
Measurement, Experimentation & Performance Analysis
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
Analytics Leadership & Cross-Functional Partnership
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
What We’re Looking For:
Experience & Education
Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, Engineering, or another quantitative discipline (Master’s degree preferred)
8+ years of experience in analytics, business intelligence, data science, or a related field
Experience leading complex analytics projects and influencing business decisions through data
Prior experience in ecommerce, digital analytics, consumer analytics, or retail environments strongly preferred
Technical Skills
Advanced proficiency in SQL and working with large-scale relational datasets
Experience working with cloud data platforms such as Redshift, BigQuery, Snowflake, or Athena
Strong proficiency with Python or R for statistical analysis, data processing, and modeling
Experience with data visualization and BI tools such as Tableau, QuickSight, Looker, or similar platforms
Strong understanding of statistical analysis and experimentation, including hypothesis testing, regression analysis, and A/B testing
Familiarity with digital analytics platforms such as Google Analytics or Adobe Analytics
Business & Analytical Skills
Strong understanding of ecommerce and marketing performance metrics such as:
Conversion rate
Customer acquisition
Demand and net sales
Contribution margin
Customer lifetime value
Retention and engagement metrics
Ability to translate complex data into clear insights and recommendations that influence business strategy
Demonstrated ability to structure ambiguous business problems into actionable analytical approaches

Employment type
Full-time

Work arrangement
No

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