Staff, Data Scientist (Pricing)

Experteer Overview In this role you will design and deploy prescriptive pricing models that directly impact profitability and customer value. You will join Walmart Global Tech’s Applied AI Data Science team to shape pricing, markdown optimization, and price recommendations at enterprise scale. You will work with cross-functional partners to translate complex data into actionable pricing strategies and measurable business outcomes. This position offers the opportunity to advance AI-driven decision making in a retail context and contribute to Walmart’s EDLP integrity. You will lead with impact, mentoring others and championing scalable, explainable AI solutions. Compensation / Benefits * Design and deploy prescriptive ML models for pricing and markdown needs * Perform elasticity analysis across large datasets to inform pricing decisions * Own the end-to-end Price Recommendation lifecycle: scoping, feature engineering, causal modeling, experimentation, and performance optimization * Develop pricing solutions using causal inference, elasticity, optimization, reinforcement learning, and deep learning techniques * Build explainable pricing systems with stakeholder-facing narratives for price decisions * Apply graph-based modeling to capture cannibalization and halo effects across product hierarchies * Establish evaluation and monitoring through backtesting, drift detection, and calibration * Collaborate with Product, Business, and Engineering to set technical direction and mentor others * Lead and contribute to AgentOps and decision-science initiatives for scenario planning and explainability Tasks * 8+ years in Data Science / Applied ML (or PhD + 5 years) with pricing, elasticity, or causal modeling experience * Production-grade optimization models with measurable financial outcomes * Strong knowledge of pricing dynamics and market/regime changes * Hands-on experience with PyTorch or TensorFlow and modern decision-focused architectures * Experience with Explainable AI and communicating model reasoning to stakeholders * Proficiency in Python and solid software engineering fundamentals (testing, CI/CD, MLOps) Key requirements * 401(k) match * stock purchase plan * paid maternity and parental leave * PTO and sick leave * health plans (medical, vision, dental) * education programs (Live Better U)

• pricing solutions using causal inference, elasticity, optimization, reinforcement learning, and deep learning techniques * Build explainable pricing systems with stakeholder-facing narratives for price decisions * Apply graph-based modeling to capture cannibalization and halo effects across product hierarchies * Establish evaluation and monitoring through backtesting, drift detection, and calibration * Collaborate with Product, Business, and Engineering to set technical direction and mentor others * Lead and contribute to AgentOps and decision-science initiatives for scenario planning and explainability Tasks * 8+ years in Data Science / Applied ML (or PhD + 5 years) with pricing, elasticity, or causal modeling experience * Production-grade optimization models with measurable financial outcomes * Strong knowledge of pricing dynamics and market/regime changes * Hands-on experience with PyTorch or TensorFlow and modern decision-focused architectures * Experience with Explainable AI and communicating model reasoning to stakeholders * Proficiency in Python and solid software engineering fundamentals (testing, CI/CD, MLOps) Key requirements * 401(k) match * stock purchase plan * paid maternity and parental leave * PTO and sick leave * health plans (medical, vision, dental) * education programs (Live Better U)