Principal Data Scientist

Walmart

. Set the technical direction, scientific roadmap, methodological standards, and technical standards for scalable measurement and optimization capabilities .

Posted 11/11/2026full-timeSan Bruno • California • United StatesLead💰 $143,000 - $286,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in machine learning, causal inference methodologies, and advanced analytics to drive measurement and optimization strategies. Proven ability to lead cross-functional initiatives and mentor data scientists while translating complex data insights into actionable business recommendations.

Highest-signal resume keywords

Machine Learning ExpertiseCausal Inference MethodologiesMedia Mix Models DevelopmentPython ProficiencyStatistical Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningCausal InferenceStatistical ModelingA/B TestingRegression AnalysisHypothesis TestingMedia Mix ModelsData AnalysisBudget PlanningScenario Analysis

Soft Skills

LeadershipMentoringCollaborationCommunicationProblem Solving

Tools & Technologies

PythonSQLGoogle BigQueryTensorFlowTableauGoogle MeridianDataproc

Industry Keywords

AnalyticsAdvertisingRetail MediaIncrementality MeasurementData Science

Tech Stack

Tools & technologies

BigQueryPythonSQLTableauTensorflow

About the role

Key responsibilities & impact

Set the technical direction, scientific roadmap, methodological standards, and technical standards for scalable measurement and optimization capabilities
Lead complex initiatives from problem definition through production, adoption, and business impact
Build Search Ghost Ads incrementality capabilities and develop and validate causal approaches
Develop and productize OMNI-Impact Pulse and Media Mix Models for budget planning, scenario analysis, optimization, and media mix recommendations
Partner with Product and Engineering on Ad Center integration and supplier-facing recommendations
Lead experimentation and causal measurement for Sponsored Product Ads and new ad product launches
Design and analyze A/B tests and apply quasi-experimental and causal inference methodologies
Extend measurement to emerging ad experiences such as Expert Videos and Seasonal Pages
Build repeatable incrementality measurement frameworks
Develop machine learning and advanced analytics solutions, including advertiser segmentation and member-level ad response prediction models
Influence strategy and decisions by partnering with Product, Engineering, Advertising, and senior business leaders
Translate complex findings and scientific tradeoffs into actionable recommendations
Mentor data scientists and elevate technical rigor through reviews, knowledge sharing, and guidance
Apply AI-driven capabilities to automate analysis and improve measurement and optimization workflows

Requirements

What you’ll need

Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 5 years' experience in an analytics-related field; or Master's degree in one of these fields and 3 years' experience; or 7 years' experience in an analytics or related field
MS or higher in a quantitative field with 10+ years of industry experience applying machine learning, statistics, and analytics to complex business problems
Experience with hypothesis testing, p-values, confidence intervals, and regression analysis
Ability to set technical direction and lead complex, cross-functional data science initiatives
Experience designing, implementing, and scaling production-grade modeling systems, including model training pipelines, evaluation, monitoring, and retraining
Hands-on experience building Media Mix Models and applying them to budget planning, optimization, and scenario analysis
Experience with saturation curves, diminishing returns, marginal ROAS, priors, and Bayesian or frequentist MMM approaches
Strong experience with causal inference and quasi-experimental methodologies, including A/B testing, power analysis, difference-in-differences, matched controls, synthetic controls, and Bayesian structural time series
2+ years of hands-on experimentation and causal ML experience
Background in machine learning and statistical modeling, including advertiser segmentation and ad response prediction
High proficiency in Python and SQL
Preferred experience with Google BigQuery and Dataproc, distributed data processing, and feature pipeline development
Preferred experience with TensorFlow or similar ML frameworks
Tableau experience is a plus
Familiarity with Google Meridian or similar MMM platforms
Familiarity with GenAI/LLM-based tools
AI/ML Engineering experience is a plus
Prior Sponsored Product Ads or retail media domain experience is a plus

Benefits

Comp & perks

Incentive awards for performance
401(k) match
Stock purchase plan
Paid maternity and parental leave
PTO
Multiple health plans
Medical, vision, and dental coverage
401(k)
Company-paid life insurance
Family care leave
Bereavement leave
Jury duty leave
Voting leave
Short-term and long-term disability
Company discounts
Military Leave Pay
Adoption and surrogacy expense reimbursement
Live Better U company-paid education benefit program
Tuition, books, and fees paid for eligible education programs
Performance-based bonus awards