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Walmart · United States

# R-2574593

United States $208,000.00 - $416,000.00 

Listed on Walmart’s official careers site. Listed as of October 18, 2026. Check that it is still open and apply there.
[Apply on Walmart’s careers site →](https://careers.walmart.com/us/en/jobs/R-2574593)

[OpenNash Jobs](https://jobs.opennash.com/) / [Walmart](https://jobs.opennash.com/companies/walmart/) / R-2574593

## Job description

### Role summary

As the Senior Director of Data Science for Commerce Foundational Models, you will lead an elite, high-caliber engineering and data science team dedicated to building Walmart’s next-generation intelligence layer. You will be responsible for the vision, strategy, and execution of large-scale foundational models trained on our massive, multi-modal dataset encompassing billions of customer touch points, transaction histories, search queries etc.

Your models will serve as the AI engine powering critical consumer facing and enterprise products across Walmart’s ecosystem, including Search, Personalization, Sponsored Ads, Conversational Commerce, and Supply Chain Forecasting.

### About the team

The AI and Data organization integrates essential capabilities to leverage AI and data as strategic assets across Walmart. It develops and manages shared platforms, intelligence, and decision systems that enhance customer experiences, empower associates, and deliver measurable business outcomes. Within this org, the Retail Intelligence group focuses on creating and deploying scalable AI models and services that bring advanced AI capabilities to Walmart’s products and operations efficiently.

The team collaborates closely with stakeholders to drive data strategy, machine learning innovation, and business insights, supporting Walmart’s commitment to operational excellence and continuous improvement.

### Key Responsibilities

Technical Vision & Strategy: Define the multi-year roadmap for Walmart’s Commerce Foundational Models. Drive the paradigm shift from siloed, domain-specific models to unified, multi-task generative architectures High-Scale Engineering Leadership: Lead a world-class team of Applied AI Researchers, Machine Learning Engineers, and Data Scientists.

### Horizontal Collaboration & Influence

Partner closely with product, engineering, and business leaders across Search, Ads, Personalization, and Customer Experience to ensure foundational models are seamlessly integrated, delivering massive business value.

### Evangelism & Adoption

Serve as the primary champion for foundational models within Walmart Global Tech.

### Minimum Qualifications

Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a highly quantitative field. 8+ years of experience directly managing and scaling high-performing data science and ML engineering teams, with at least 3+ years managing managers. Proven track record of designing, training, and deploying deep learning models in production at massive scale Deep understanding of distributed training frameworks

### Preferred Qualifications

Ph.D. in CS, ML, or a related field with a strong publication record in top-tier AI/ML conferences Domain Expertise in Commerce/RecSys and experience building Generative Recommenders, Hierarchical Sequential Transducers(HSTU) or sequence-based models for user behavior representation. Deep knowledge of low-latency inference optimization techniques, real-time retrieval. At Walmart, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet.

Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more.

You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable. For information about PTO, see [https://one.walmart.com/notices](https://one.walmart.com/notices). Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities.

Programs range from high school completion to bachelor's degrees, including English Language Learning and short-form certificates. Tuition, books, and fees are completely paid for by Walmart. Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms. For information about benefits and eligibility, see One.Walmart.

### Sunnyvale, California US-11656

The annual salary range for this position is $208,000.00 - $416,000.00 Bentonville, Arkansas US-10735: The annual salary range for this position is $160,000.00 - $320,000.00 Additional compensation includes annual or quarterly performance bonuses.

Additional compensation for certain positions may also include: - Stock

## Qualifications

### Option 1

Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 7 years' experience in an analytics related field.

### Option 2

Master’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field.

### Option 3

9 years' experience in an analytics or related field. 3 years' supervisory experience.

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Aug 21, 2026
- Last checked: Oct 18, 2026
- Listed for: 58 days
- Location: United States
- Pay: $208,000.00 - $416,000.00[Apply on Walmart’s careers site →](https://careers.walmart.com/us/en/jobs/R-2574593)

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