Head of Product Data & Analytics - Supply Chain Digital Enablement

About the Role

The Head of Product Data & Analytics, Supply Chain Digital Enablement (North America) leads the data discipline within the Product organization, overseeing the analysts and data scientists embedded in empowered product teams. This leader is responsible for how teams use data to understand behavior, measure progress, experiment confidently, and discover new opportunities.

You will build and scale a modern product insights capability that brings together analytics, data science, experimentation, instrumentation, and decision support. You will ensure teams move from opinion‑driven to evidence‑informed, while partnering closely with Design and Research to connect what users do with why they do it.

This role is deeply cross‑functional. You will work alongside Product, Design, and Engineering leaders to define metrics, build measurement frameworks, instrument features, run experiments, and develop models that create both internal insight and customer‑facing value.

• Hire, develop, and lead analysts, data scientists, and experimentation specialists embedded in product teams
• Define roles, standards, and career paths for analytics and data science
• Create a culture rooted in curiosity, rigor, and clear storytelling

• Ensure teams use data to understand behavior, measure outcomes, and evaluate ideas
• Guide the use of experiments, prototypes, and causal analysis to reduce risk
• Enable product leaders to shift from feature roadmaps to outcome‑based KPIs and scorecards

• Establish KPIs, guardrails, and leading indicators for each product area, including service levels, forecast accuracy, throughput, inventory health, and cost‑to‑serve
• Operationalize experimentation practices including A/B tests, holdouts, and causal inference
• Ensure products are instrumented correctly so teams are never “flying blind”

• Oversee user analytics, customer analytics, funnels, cohorts, and retention analyses
• Guide business and product economics analytics such as LTV, churn, and unit economics
• Ensure data quality, accuracy, and usability across platforms

• Guide segmentation, forecasting, clustering, and propensity modeling
• Partner with product and engineering to embed predictive and adaptive models into product experiences
• Ensure ML models are monitored, evaluated, and continuously improved

• Coach PMs, designers, and engineers to be confident, data‑literate decision makers
• Promote experimentation and analytics as routine parts of product work
• Scale learnings and insights across the organization to build shared knowledge

• Size opportunities, prioritize bets, and guide investment decisions using data
• Provide scenario modeling and forecasting for portfolio sequencing
• Represent the data and insights perspective in senior forums

• 10+ years of experience in analytics, data science, or related fields, with at least five years leading teams in digital product environments
• Bachelor's degree in data science, statistics, economics, computer science, or related field
• Experience embedding analysts and/or data scientists within cross‑functional product or engineering teams
• Strong foundation in product analytics including behavioral data, funnels, cohorts, and retention
• Deep experience with experimentation including A/B testing, test design, and interpretation
• Familiarity with data science techniques such as clustering, regression, propensity modeling, and recommendations
• Fluency with modern data platforms including warehouses, event tracking, BI tools, and experimentation frameworks
• Ability to translate complex analyses into clear, actionable insights for product and executive audiences
• Strong collaboration and influence skills across Product, Engineering, and Design

• Advanced degree in data science, statistics, economics, computer science, or a related field…