This role pays less than
65%
of similar roles. Most pay
$162,000–$228,950
— the shaded band above.
At the midpoint, this role pays about
$165k
versus about
$195k
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) Senior Manager, Data Science (AI Technical Lead) serves as the technical lead for the Customer Engagement Services team, focusing on omni-channel returns. This role involves architecting autonomous AI systems that utilize Causal Inference, Deep Learning, and Large Language Models to analyze structured transaction data alongside unstructured customer feedback like chat logs and reviews. The position requires building predictive models to identify root causes of friction and designing MLOps frameworks to monitor model performance and hallucination rates. Key responsibilities include mentoring a team of data scientists, enforcing engineering standards such as Git version control and unit testing, and writing high-performance Python and PySpark code. The role addresses the complex problem of transforming reactive return processes into proactive, personalized customer interventions using advanced techniques like time-series forecasting, anomaly detection, and causal frameworks to improve the overall retail experience.
Architect end-to-end algorithmic frameworks for proactive returns intelligence using Causal Inference, Deep Learning, and LLMs.
Apply Causal AI to identify the root causes of customer behavior and evaluate counterfactual scenarios.
Mentor a team of data scientists to transition from local scripts to scalable, production-ready code.
Enforce engineering standards including Git version control, rigorous code reviews, and comprehensive unit/integration testing.
Design MLOps frameworks to monitor real-time model performance, data drift, and LLM hallucination rates.
Translate ambiguous business objectives into concrete, executable AI roadmaps for executive leadership.
Write high-performance Python and PySpark code for mission-critical recommendation engine components.
What we're looking for
Must have a Bachelor’s degree with 5 years of experience, a Master’s degree with 3 years of experience, or 7 years of relevant experience in analytics.
Advanced degree (MS/PhD) in a quantitative field such as Computer Science, Statistics, Operations Research, Economics, or Applied Mathematics is preferred.
Expert-level proficiency in Python and SQL for developing high-performance, fault-tolerant code.
Experience with PySpark to manage and process large, petabyte-scale datasets.
Expertise in advanced modeling including time-series forecasting, anomaly detection, and causal inference frameworks.
Proficiency in NLP and LLMs to extract sentiment and features from unstructured data.
Strong software engineering skills including Git version control, CI/CD integration, and unit/integration testing with pytest.
Experience with MLOps tools such as Docker, Kubernetes, and cloud infrastructure (GCP or AWS).
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
Python
AWS
Spark
H2O
Conda
Machine Learning
Scala
R
Deep Learning
Time Series
Sentiment Analysis
Clustering
Classification
Relational Databases
Big Data