Senior Manager, Advanced Analytics

Walmart Walmart · Retail · San Bruno, CA

Senior Manager, Advanced Analytics at Walmart to lead analytical initiatives improving investment discipline, growth strategy, and decision-making across Marketplace and eCommerce. Focuses on building scalable frameworks for incrementality measurement, investment efficiency, marketing allocation, and translating findings into business actions. Requires strong leadership in experimentation, causal inference, forecasting, and business partnering, with experience in ambiguous environments and influencing senior stakeholders.

What you'd actually do

  1. Partner with senior leaders across Marketplace, Marketing, Finance, Product, Merchandising, WMC, and Data Science to understand business goals, diagnose key challenges, and develop analytical solutions that drive measurable impact.
  2. Translate ambiguous business questions into structured analytical problems, including investment incrementality, marketing and incentive overlap, seller and item prioritization, customer cohort targeting, and the right balance between offer exposure, price competitiveness, and customer experience.
  3. Provide actionable recommendations to senior leadership based on advanced analytics, experimentation, and causal inference.
  4. Focus efforts on opportunities with the highest business impact and help leadership make trade-offs across growth, efficiency, and customer experience.
  5. Lead the design, execution, and interpretation of incrementality studies, A/B tests, quasi-experiments, and causal inference frameworks.

Skills

Required

  • SQL
  • Python or R
  • experimentation
  • causal inference
  • forecasting
  • econometric modeling
  • marketing/investment measurement
  • translating analytical findings into executive-level recommendations
  • cross-functional business, product, finance, engineering, or data science stakeholder partnership
  • people leadership
  • coaching
  • prioritization
  • performance development

Nice to have

  • Master's degree or PhD in Economics, Statistics, Data Science, Operations Research, Engineering, Computer Science, or a related quantitative field
  • marketplace, eCommerce, retail, advertising, marketing analytics, pricing, incentives, or seller growth programs experience
  • difference-in-differences
  • synthetic controls
  • uplift modeling
  • meta-learners
  • propensity-based methods
  • marketing effectiveness
  • incrementality testing
  • ROAS measurement
  • investment optimization
  • diminishing returns curves
  • saturation models
  • marginal ROI frameworks
  • production-ready analytics assets
  • dashboards
  • automated diagnostics

What the JD emphasized

  • move beyond reporting and diagnostics to build decision frameworks that directly shape business strategy, resource allocation, and operating discipline
  • lead high-impact analytical initiatives
  • lead the design, execution, and interpretation of incrementality studies, A/B tests, quasi-experiments, and causal inference frameworks
  • develop approaches to measure the true impact of business investments
  • apply methods such as randomized experiments, difference-in-differences, synthetic controls, propensity-based approaches, uplift modeling, meta-learners, interrupted time series, and other causal techniques where appropriate
  • build repeatable experimentation playbooks
  • build forecasting and econometric models
  • develop diminishing returns curves, transfer functions, saturation models, and marginal ROI frameworks
  • support annual and quarterly planning by building analytical tools that estimate expected returns, identify risks, and guide spend allocation across programs and channels
  • evaluate new analytical techniques and determine when they are appropriate for business use, balancing technical rigor with interpretability, speed, and operational feasibility
  • ensure analytical outputs are robust, explainable, and usable by business stakeholders
  • lead development of analytical datasets that connect investments, exposures, seller behavior, item performance, customer outcomes, and financial returns
  • identify gaps in instrumentation, data quality, attribution logic, and measurement methodology
  • democratize insights through scalable reporting, Looker dashboards, automated diagnostics, and executive-ready business reviews