below marketmost similar roles pay hereabove market
This role pays less than
66%
of similar roles. Most pay
$175,500–$261,667
— the blue band above.
At the midpoint, this role pays about
$195k
versus about
$219k
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
719 open roles
on FindRole.
Listed pay typically runs
$117,000–$234,000
across 592 roles with salary data.
As the (USA) Director, Data Science for the Walmart Data Ventures Tech team, you will lead the development and deployment of production-grade, end-to-end supplier-facing AI systems. You will manage and mentor a team of data scientists, machine learning engineers, and software engineers to build scalable solutions that optimize operations and unlock new business models. Your daily responsibilities include owning the full lifecycle from research to production, driving technical innovation in generative AI, agentic intelligence, B2B recommendation platforms, measurement, and causal inference. You will utilize skills in Python, Spark, Scala, or R, along with open source frameworks like scikit learn, tensorflow, and torch. This role solves complex enterprise retail challenges by transforming extensive data into actionable insights and recommendations for a global network of suppliers.
Lead the end-to-end lifecycle of production-grade AI systems from research to deployment.
Scale advanced capabilities in generative AI, agentic intelligence, and causal inference.
Manage and mentor a high-performing team of data scientists, machine learning engineers, and software engineers.
Develop and deploy B2B recommendation platforms to solve complex enterprise retail challenges.
Align the AI roadmap with overarching business strategies and supplier needs.
Translate complex data insights into clear business strategies to influence the product roadmap.
Optimize operations and develop new business models for the global supplier network.
What we're looking for
Obtain a Bachelor's degree in a related field with 6 years of analytics experience, a Master's with 4 years, or 8 years of experience.
Lead the end-to-end lifecycle of production-grade AI systems from research to deployment.
Scale advanced capabilities in generative AI, agentic intelligence, B2B recommendation platforms, measurement, and causal inference.
Manage and mentor a high-performing team of data scientists, machine learning engineers, and software engineers.
Influence the product roadmap by translating complex data insights into clear business strategies.
Possess a PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, or Econometrics (preferred).
Demonstrate proficiency in Python, Spark, Scala, or R through successful assessment completion (preferred).
Experience with open source frameworks like scikit-learn, tensorflow, or torch (preferred).
Machine Learning
Python
SQL
Spark
Scala
R
scikit learn
TensorFlow
Data Modeling
Optimization Models
Data Visualization
Statistics
Econometrics
Operations Research
WCAG) 2.2 AA
Machine Learning
Python
SQL
Java
Spark
Scala
R
scikit learn
TensorFlow
Data Visualization
Data Strategy
Data Governance
Optimization Models
Statistics
Econometrics
Model Validation
Python
SQL
Java
Machine Learning
Operations Research
Optimization
Simulation
Spark
Scala
R
TensorFlow
scikit learn
data visualization
data strategy
WCAG) 2.2 AA
Machine Learning
Deep Learning
Python
Spark
TensorFlow
scikit learn
Scala
R
Distributed Training
Low-latency Inference
RecSys
Optimization Models
WCAG) 2.2 AA
Data Science
Statistics
Operations Research