This role pays less than
76%
of similar roles. Most pay
$198,000–$269,087
— the shaded band above.
At the midpoint, this role pays about
$195k
versus about
$234k
for comparable roles.
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
184 open roles
on FindRole.
Listed pay typically runs
$117,000–$234,000
across 180 roles with salary data.
(USA) Director, Data Science leads the strategy, development, and delivery of next-generation Price Recommendation solutions while managing a high-performing team of Data Scientists and Machine Learning Engineers. This leader defines multi-year roadmaps, influences executive strategy, and partners with Product, Engineering, Merchandising, and Business teams to build AI and ML products that improve pricing decisions and customer value. The role involves overseeing the end-to-end delivery of scalable models for demand forecasting, price elasticity modeling, causal inference, recommendation systems, reinforcement learning, optimization, and experimentation through A/B testing. Key technical competencies include proficiency in Python, Spark, Scala, or R, along with experience using open-source frameworks like scikit learn, tensorflow, and torch. The position focuses on solving complex pricing problems by translating advanced machine learning methodologies into actionable business outcomes within the retail domain to enhance overall performance at scale.
Define and own the multi-year vision and roadmap for Price Recommendation capabilities aligned with business objectives.
Lead, mentor, and grow a high-performing team of Data Scientists and Machine Learning Engineers.
Translate complex technical concepts into clear business outcomes for executive leadership and cross-functional partners.
Manage the end-to-end delivery of ML products from initial ideation through production deployment and measurement.
Provide technical direction on methodologies including demand forecasting, price elasticity modeling, and causal inference.
Identify opportunities to leverage AI, machine learning, and optimization to improve pricing decisions at scale.
Ensure all deployed solutions are scalable, reliable, explainable, and meet high standards of operational excellence.
Establish success metrics and continuously monitor model performance to drive measurable business impact.
What we're looking for
A Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or a related field with 6 years of experience in an analytics field.
A Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or a related field with 4 years of experience in an analytics field.
At least 8 years of experience in an analytics or related field.
Expertise in machine learning methodologies including demand forecasting, price elasticity modeling, causal inference, and reinforcement learning.
Experience in optimization models, experimentation, and A/B testing.
Proficiency with open source frameworks such as scikit learn, tensorflow, or torch.
Ability to perform successfully in assessments involving Python, Spark, Scala, or R.
Experience in supervisory roles and leading teams of data scientists and machine learning engineers.
Machine Learning
Python
SQL
Java
Spark
Scala
R
scikit learn
TensorFlow
Data Visualization
Optimization Models
Data Governance
Statistics
Econometrics
Operations Research
WCAG) 2.2 AA