below marketmost similar roles pay hereabove market
This role pays less than
70%
of similar roles. Most pay
$163,500–$234,112
— the blue band above.
At the midpoint, this role pays about
$165k
versus about
$199k
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
723 open roles
on FindRole.
Listed pay typically runs
$117,000–$234,000
across 590 roles with salary data.
Senior Manager, Data Science - Inventory Capabilities joins the Inventory Capabilities team as an individual contributor to drive next-generation inventory science and strategy. The role involves designing, implementing, and scaling algorithms to optimize inventory placement, safety stock targets, forecasting, and exits. You will analyze large-scale datasets to refine model inputs, improve accuracy, and enhance scalability across a global network. Key responsibilities include applying advanced techniques in optimization, probabilistic forecasting, and machine learning to improve efficiency and resilience. You will use modern programming languages including Python, PySpark, R, and SQL, alongside open-source frameworks like scikit-learn, tensorflow, and torch. The work addresses complex retail and supply chain problems, specifically focusing on multi-echelon optimization, dynamic inventory placement, and omni-channel fulfillment to improve customer availability and delivery speed.
What does a Data Science Manager earn?
Median $211200 from 40 postings across 10 companies.
Design and deliver new models for forecasting, placement, inventory targets, safety stock, and exits.
Apply advanced optimization, probabilistic forecasting, and machine learning techniques to improve global network efficiency.
Analyze large-scale datasets to refine model inputs, cost structures, and constraints for improved scalability.
Lead projects from framing business problems to building, validating, and deploying models with engineering teams.
Develop scenario modeling, dynamic inventory placement, and multi-echelon optimization for omni-channel fulfillment.
Translate complex data science into actionable strategies for Merchandising, Supply Chain, and Tech partners.
What we're looking for
Option 1: Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, IT, or related field and 5 years of analytics experience.
Option 2: Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, IT, or related field and 3 years of analytics experience.
Option 3: 7 years of experience in an analytics or related field.
Strong expertise in applied data science and advanced analytics including optimization, forecasting, simulation, and machine learning.
Experience implementing data science models using Python, PySpark, R, and SQL.
Extensive knowledge of eCommerce, retail, and supply chain domains and related information systems.
Experience with advanced analytical modeling tools, network optimization, and long-range planning.
PhD in Machine Learning, Computer Science, IT, Operations Research, Statistics, Applied Mathematics, or Econometrics (preferred).
Python
Machine Learning
Mathematical Optimization
SQL
NoSQL
Spark
Scala
R
scikit learn
TensorFlow
Operations Research
Statistics
Data Visualization
Data Governance
WCAG) 2.2 AA
Python
SQL
Java
Machine Learning
Operations Research
Optimization
Simulation
Spark
Scala
R
TensorFlow
scikit learn
data visualization
data strategy
WCAG) 2.2 AA
Python
SQL
Machine Learning
Spark
Scala
R
scikit learn
TensorFlow
Data Engineering
Data Visualization
Exploratory Data Analysis
Feature Engineering
Optimization Models
WCAG) 2.2 AA