below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$150,686–$229,925.
Based on 240 similar postings.
Employer
About Walmart
Walmart Inc. is the world''s largest retailer by revenue, operating a chain of hypermarkets, discount department stores, and grocery stores, as well as a growing e-commerce presence through Walmart.com. Industry: General Merchandise & Grocery Retail
Walmart currently has
825 open roles
on FindRole.
Listed pay typically runs
$121,000–$242,000
across 473 roles with salary data.
JOB TITLE: Staff, Data Scientist (Pricing/Reinforcement Learning)
The Staff, Data Scientist (Pricing/Reinforcement Learning) joins the Applied AI Data Science team to develop scalable algorithms for the pricing organization. You will design and deploy prescriptive machine learning models to address high-impact pricing and markdown needs while owning the end-to-end price recommendation lifecycle. Key responsibilities include performing elasticity analysis, conducting causal modeling, and building explainable pricing systems. You will utilize technologies including Python, PyTorch, TensorFlow, Spark, and R to implement deep learning, reinforcement learning (PPO, DQN), and multi-armed bandits. The role involves solving complex retail challenges such as demand sensing, price-response curves, and cannibalization effects using graph-based modeling. You will collaborate with cross-functional teams to provide model interpretability and drive best practices in AgentOps for chat-based price explainability and scenario planning.
What does a Data Scientist earn in California?
Median $214500 from 114 postings across 26 companies.
Design and deploy prescriptive ML models to address high-impact pricing and markdown needs.
Perform elasticity analysis across large data sets and category segments to drive pricing decisions.
Own the end-to-end price recommendation lifecycle including scoping, feature engineering, and A/B testing.
Develop advanced optimization solutions using Causal Inference, Reinforcement Learning, and Deep Learning.
Build explainable pricing systems to provide model interpretability and narratives for business stakeholders.
Apply graph-based modeling to capture cannibalization and halo effects across product hierarchies.
Establish evaluation and monitoring protocols including backtesting, drift detection, and calibration.
Build Agentic workflows to enable chat-based price explainability and "what-if" scenario planning.
What we're looking for
Must have a Bachelor's degree in a related field and 4 years of analytics experience, a Master's degree and 2 years of experience, or 6 years of experience.
Must have 8+ years of experience in Data Science/Applied ML or a PhD plus 5 years of experience.
Must have deep hands-on exposure to pricing, elasticity, or causal modeling.
Must have demonstrated experience delivering production-grade optimization models with measurable financial outcomes.
Must have strong knowledge of pricing dynamics, including seasonality, competitor indexing, and promotional impact.
Must have hands-on experience with PyTorch or TensorFlow and strong coding skills in Python.
Must have practical experience with Explainable AI (XAI) and communicating complex model reasoning to non-technical stakeholders.