This role pays less than
78%
of similar roles. Most pay
$204,843–$278,000
— the shaded band above.
At the midpoint, this role pays about
$195k
versus about
$241k
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.
As Director, Data Science - Earnings Innovation & Automation, you will join the Spark Driver Earnings team to lead the transformation of independent contractor earnings through advanced data science and automation. You will manage a high-performing tiger team to prototype and scale machine learning solutions for anomaly detection, tax classification, and risk monitoring. Your daily work involves developing intelligent automation using ML and GenAI to improve accuracy and reduce manual effort in calculating, diserbinging, and reporting global earnings. To succeed, you must possess expertise in Python, SQL, and modern frameworks like TensorFlow or PyTorch, alongside experience with LLMs and model governance. This role addresses critical business problems involving compliance-heavy domains such as fintech, payments, and tax processes to ensure data integrity and operational rigor for a global contractor network while ensuring all AI solutions remain transparent and auditable.
Define and lead AI/ML strategies for contractor earnings, tax processes, and compliance monitoring.
Lead a high-performing data science team to prototype and scale innovative solutions.
Develop intelligent automation using machine learning and generative AI to reduce manual effort.
Implement ML models for anomaly detection, tax classification, and risk management.
Ensure all AI solutions are transparent, auditable, and compliant with regulatory requirements.
Collaborate with Product, Engineering, and Operations teams to move solutions into production.
Drive data science initiatives that deliver measurable improvements in accuracy and operational efficiency.
What we're looking for
Candidates must have 10–12+ years of experience in data science, ML, or AI.
Candidates must have 3–5+ years of experience leading high-performing teams.
Applicants must meet one of three education/experience paths: a Bachelor's with 6 years of analytics experience, a Master's with 4 years, or 8 years of experience.
Candidates must possess deep technical expertise in Python, SQL, and modern ML frameworks like TensorFlow or PyTorch.
Experience with GenAI and LLMs applied to real-world business problems is required.
Candidates should have a track record of building production-grade ML/AI solutions in complex environments.
Knowledge of model governance, explainability, and risk management is required.
Preferred experience includes fintech, payments, tax, or compliance-heavy domains.
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
Machine Learning
Generative AI
LLM
Python
Spark
Scala
R
scikit learn
TensorFlow
Optimization
Analytics
Simulation
Data Science
Decision Intelligence
Digital Twins
WCAG) 2.2 AA