below marketmost similar roles pay hereabove market
This role pays less than
62%
of similar roles. Most pay
$162,000–$218,750
— the blue band above.
At the midpoint, this role pays about
$165k
versus about
$190k
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
825 open roles
on FindRole.
Listed pay typically runs
$121,000–$242,000
across 473 roles with salary data.
JOB TITLE: (USA) Senior Manager, Data Science (AI Technical Lead) – Next-Gen Customer Engagement & Returns
The Senior Manager, Data Science (AI Technical Lead) joins the Customer Engagement Services team to architect an autonomous, intelligent ecosystem for omni-channel returns. This role involves designing end-to-end algorithmic frameworks to predict, personalize, and prevent friction in the return journey. You will build proactive returns intelligence agents by fusing Causal Inference, Deep Learning, and Large Language Models to analyze structured transaction data and unstructured customer feedback. Key responsibilities include mentoring data scientists, enforcing engineering rigor through Git, unit testing, and CI/CD pipelines, and developing MLOps frameworks to monitor data drift and LLM hallucinations. You will utilize Python, SQL, PySpark, and frameworks like scikit-learn, TensorFlow, or Torch to solve complex retail supply chain logistics and improve consumer behavior outcomes.
Architect the end-to-end algorithmic framework for proactive returns intelligence using Causal Inference, Deep Learning, and LLMs.
Apply Causal AI to analyze return behaviors and determine the impact of specific interventions like discounts.
Mentor data scientists to transition from local scripts to scalable, production-ready code with strict version control and testing.
Design MLOps and monitoring frameworks to track real-time model performance, data drift, and LLM hallucination rates.
Translate ambiguous business objectives into concrete, executable AI roadmaps and technical strategies.
Write high-performance, fault-tolerant Python and PySpark code for mission-critical recommendation engine components.
What we're looking for
Obtain a Bachelor's degree with 5 years of analytics experience, a Master's degree with 3 years of analytics experience, or 7 years of analytics experience.
Possess deep expertise in time-series forecasting, anomaly detection, and modern predictive modeling.
Demonstrate proven ability to apply causal inference frameworks to observational data.
Utilize Natural Language Processing and Large Language Models to extract features from unstructured data.
Maintain expert-level fluency in Python and SQL.
Have strong hands-on architecture experience with PySpark and petabyte-scale datasets.
Demonstrate extensive experience with Unit/Integration Testing (pytest) and advanced Git management.
Possess experience with Docker/Kubernetes, cloud infrastructure (GCP or AWS), and mentoring technical teams (preferred).
Tableau
Power BI
SQL
Python
Spark
Scala
R
Data Modeling
Data Visualization
Big Data
Data Governance
Geospatial Tools
Data Quality Management
Exploratory Data Analysis
Statistics
AI Tools