Senior Manager, Data Science - Inventory Capabilities

Walmart • Bentonville, AR

86d • $110,000 - $220,000

About The Position

We're looking for a Sr. Manager Data Scientist to join Walmart's Inventory Capabilities team, driving the next generation of inventory science and strategy. This individual contributor role will shape models and systems that maximize our Customer Value Proposition (CVP) by ensuring the right items are in the right place, at the right time, in the right quantity — at the lowest cost. You'll design, implement, and scale algorithms that connect data science, advanced analytics, and business execution to transform Walmart's inventory placement, safety stock targets, forecasting, and exits. This is a high-visibility role where your work directly impacts customer availability, delivery speed, cost to serve, and sales growth. This position is based in Bentonville, AR at Walmart's new Home Office Campus.

Requirements

• Strong expertise in applied data science and advanced analytics (optimization, forecasting, simulation, machine learning).
• Comfortability operating at both strategic and technical depth — from building models to influencing enterprise priorities.
• Experience simplifying complex science for senior leaders and business partners to drive adoption and decision-making.
• Ability to excel in ambiguous, high-pressure environments with multiple stakeholders and competing priorities.
• A passion for solving global-scale inventory optimization challenges that directly improve customer experience.
• MBA, MS, or PhD in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Operations Management, or Supply Chain Management.
• Experience implementing data science models using modern programming languages (e.g., Python, PySpark, R) and using large dataset mining tools (e.g., SQL).
• Experience with advanced analytical modeling tools, network optimization, and long-range planning.
• Extensive experience or knowledge of eCommerce, retail and supply chain domains and related information systems.

Nice To Haves

• Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics.
• Successful completion of one or more assessments in Python, Spark, Scala, or R.
• Supervisory experience.
• Using open source frameworks (for example, scikit learn, tensorflow, torch).
• Knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility.

Responsibilities

• Analyze large-scale datasets to refine model inputs (forecasts, cost structures, constraints) and improve accuracy and scalability.
• Design and deliver new models and algorithms across forecasting, placement, inventory targets, safety stock, and exits to optimize cost, speed, and customer experience.
• Apply advanced techniques in optimization, probabilistic forecasting, and ML to improve efficiency and resilience across Walmart's global network.
• Lead projects from framing business problems, to building and validating models, to partnering with engineering for deployment.
• Translate science into strategy, working with Merchandising, Supply Chain, and Tech partners to align on priorities and deliver measurable impact.
• Advance scenario modeling, dynamic inventory placement, multi-echelon optimization, and placement orchestration for omni-channel fulfillment.

Benefits

• Competitive pay and performance-based bonus awards.
• Health benefits including medical, vision and dental coverage.
• Financial benefits including 401(k), stock purchase and company-paid life insurance.
• Paid time off benefits including PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting.
• Short-term and long-term disability.
• Company discounts.
• Military Leave Pay.
• Adoption and surrogacy expense reimbursement.
• Live Better U education benefit program for associates.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Industry: General Merchandise Retailers
• Education Level: Master's degree