below marketmost similar roles pay hereabove market
This role pays more than
95%
of similar roles. Most pay
$157,425–$235,250
— the blue band above.
At the midpoint, this role pays about
$310k
versus about
$196k
for comparable roles.
Based on 240 similar postings.
Employer
About Levi Strauss & Co
Levi Strauss & Co. is one of the world''s largest apparel companies, known for its iconic Levi''s brand of denim jeans, jackets, and related clothing and accessories sold globally. Industry: Apparel & Fashion
The Head of Global Analytics & Insights leads the Global Analytics & Insights organization to transform enterprise data into commercial decisions. This leader will build a modern capability combining performance reporting, decision science, experimentation, consumer insight, and AI-enabled analytics. Key responsibilities include defining a multi-year strategy, partnering with executives to frame ambiguous problems, and translating sell-through, pricing, and loyalty data into actionable recommendations. The role involves modernizing insight delivery through governed self-service, reusable decision products, and conversational analytics while embedding AI and agentic workflows responsibly. The successful candidate will utilize SQL and familiarity with Looker, Tableau, Power BI, and dbt. This position solves complex business problems across assortment, pricing, markdown, and channel mix within a multi-channel retail environment spanning direct-to-consumer and wholesale channels.
Define a multi-year analytics strategy and prioritize high-value decision opportunities across global commercial domains.
Partner with executives to frame ambiguous problems and establish shared accountability for measurable business outcomes.
Translate complex data into decision-ready recommendations regarding pricing, assortment, promotions, and consumer loyalty.
Transition the organization from static reporting toward governed self-service, reusable decision products, and conversational analytics.
Embed AI and agentic workflows into insight delivery with clear evaluation criteria and human oversight.
Expand the use of experimentation, causal measurement, and scenario planning to foster a test-and-learn culture.
Establish an operating model for intake, prioritization, service levels, and value-tracking practices.
Lead and develop a team of managers and analytics talent across multiple business domains.
What we're looking for
12+ years of progressive experience in analytics, insights, or decision science.
5+ years of experience leading an analytics organization.
3+ years of experience leading managers across multiple business domains.
Leadership experience in multi-channel retail, consumer goods, apparel, or another complex consumer business.
Proven record of influencing commercial and P&L outcomes through analytics.
Experience building or evolving an analytics organization, operating model, and capability portfolio.
Fluency in experimentation, measurement, and advanced analytics with the ability to communicate limitations clearly.
Working knowledge of large language models, AI agents, and evaluation approaches.
Experience in strategy consulting, advanced analytics consulting, or a high-growth consumer or technology company (preferred).
Proficiency with SQL and familiarity with modern BI, semantic-layer, and analytics engineering platforms such as Looker, Tableau, Power BI, and dbt (preferred).
Experience establishing analytics product management, model or AI evaluation, responsible AI, or value-realization practices (preferred).
Knowledge of apparel or lifestyle retail, including seasonal cadence and global operations (preferred).
Business Analytics
Business Intelligence
Data Science
AI
Root Cause Analysis
Data Engineering
Application Development
Analytics Solutions
Statistics
Mathematics
Computer Science
Finance Analytics
Operations Analysis
AI
ML
Generative AI
Agentic AI
Python
R
Snowflake
Databricks
MLOps
A/B Testing
Causal Inference
Retrieval-Augmented Generation
Data Architecture
Agile
Model Governance
Data Science
Data Engineering
Data Architecture
Business Intelligence
Machine Learning
Artificial Intelligence
Cloud Architecture
Semantic Modeling
Data Quality
Statistical Methods
Data Products
Reporting & Insights
Automation
Data Strategy