Staff, Data Scientist (Pricing/Reinforcement Learning)

Experteer Overview In this role you will design and deploy prescriptive ML models to optimize pricing and markdown decisions for Walmart’s pricing organization. You will own the end-to-end price recommendation lifecycle and partner with cross-functional teams to drive measurable financial outcomes. You’ll work with a multidisciplinary Applied AI group on scalable, AI-driven solutions across forecasting, optimization, and experimentation. This is a hands-on, impact-focused role at enterprise scale with opportunities to shape pricing strategy and explainability. You will join a collaborative team that values rigorous analytics, experimentation, and mentorship. Compensation / Benefits * Design and deploy prescriptive ML models for pricing and markdown needs * Perform elasticity analysis across large datasets to inform data-driven pricing decisions * Own the end-to-end Price Recommendation lifecycle including feature engineering, causal modeling, experimentation, and performance optimization * Develop pricing and optimization solutions using causal inference, elasticity, reinforcement learning, and deep learning * Build explainable pricing systems with stakeholder-facing narratives * Apply graph-based modeling to capture cannibalization and halo effects * Establish evaluation and monitoring with backtesting, drift detection, and calibration * Drive AgentOps practices for chat-based price explainability and what-if scenarios * Collaborate with Product, Business, and Engineering to set technical direction and mentor junior team members Tasks * 8+ years in Data Science / Applied ML (or PhD + 5 years) * Hands-on experience delivering production-grade optimization models with measurable financial outcomes * Strong knowledge of pricing dynamics: seasonality, competitor indexing, promotions, regime changes * Hands-on experience with deep learning frameworks (PyTorch or TensorFlow) * Practical experience with Explainable AI and communicating model reasoning to non-technical stakeholders * Excellent Python coding skills and solid software engineering fundamentals (testing, CI/CD, MLOps) Key requirements * 401(k) match * stock purchase plan * paid maternity and parental leave * PTO and paid sick leave * health plans (medical, vision, dental) * Live Better U education benefit

for * Develop pricing and optimization solutions using causal inference, elasticity, reinforcement learning, and deep learning * Build explainable pricing systems with stakeholder-facing narratives * Apply graph-based modeling to capture cannibalization and halo effects * Establish evaluation and monitoring with backtesting, drift detection, and calibration * Drive AgentOps practices for chat-based price explainability and what-if scenarios * Collaborate with Product, Business, and Engineering to set technical direction and mentor junior team members Tasks * 8+ years in Data Science / Applied ML (or PhD + 5 years) * Hands-on experience delivering production-grade optimization models with measurable financial outcomes * Strong knowledge of pricing dynamics: seasonality, competitor indexing, promotions, regime changes * Hands-on experience with deep learning frameworks (PyTorch or TensorFlow) * Practical experience with Explainable AI and communicating model reasoning to non-technical aa narratives * Excellent Python coding skills and solid software engineering fundamentals (testing, CI/CD, MLOps) Key requirements * 401(k) match * stock purchase plan * paid maternity and parental leave * PTO and paid sick leave * health plans (medical, vision, dental) * Live Better U education benefit