Staff, Data Scientist

• Position Summary...
• Role Overview and Strategic Impact The Staff Data Scientist within the Walmart US Decision Sciences team is a high-impact technical leader and a vital "thinking partner" to the US Store Operations executive team.

Operating at the critical intersection of sophisticated data science and high-stakes retail strategy, this role is responsible for architecting the future of retail operations. You will not merely execute technical tasks; you will serve as a strategic bridge, translating complex methodologies into the actionable intelligence required to navigate the world's largest retail landscape. Success in this position requires a masterful synthesis of machine learning, operations research, and sharp business acumen. The Staff Data Scientist's primary value lies in the ability to embrace and resolve extreme ambiguity—defining the problem before solving it. By moving beyond one-off reports toward "platform thinking," you will create scalable solutions that transform vast datasets into a narrative for strategic change. This role is fundamental to modernizing US Store Operations, ensuring that every operational shift is backed by rigorous data-based evidence and prescriptive foresight.

• What you'll do...
• Key Responsibilities and Value Drivers
• The responsibilities of a Staff Data Scientist extend far beyond technical execution to include organizational mentorship and the setting of technical standards. As a senior leader, you will exert cross-functional influence to deliver measurable outcomes that define the standard for excellence within the Decision Sciences team. +

• Strategic Partnership & Stakeholder Management:

• By partnering directly with US Store Operations leadership, you will manage expectations and align technical roadmaps with core business priorities. This ensures that data science initiatives are never siloed but are instead driving the broader organizational roadmap, influencing how leadership identifies and pursues new ways to improve operational outcomes. +
• Advanced Analytical Modeling (Causal & Predictive):
• You will apply advanced causal inference modeling and deploy supervised/unsupervised machine learning models to identify hidden variables. By identifying true causal relationships rather than simple correlations, you move the organization from reactive analysis (what happened?) to prescriptive action (what will happen if we change X?), allowing for high-certainty strategic interventions. +

• Metric Optimization & Deep Dives:

• You will conduct exhaustive deep dives into metric fluctuations to provide concrete, data-backed recommendations for Store Operations. These deep dives transform noise into signals, preventing reactive decision-making and ensuring that US Store Operations leadership invests human and financial resources only in high-certainty interventions. +

• Technical Standard-Setting:

• A non-negotiable requirement of this role is experience in delivery of production-quality, scalable, and maintainable code. As a Staff-level individual contributor, you set the bar for the entire team, ensuring that models are robust, reusable tools capable of performing at Walmart's massive global scale.
• Core Qualifications and Technical Proficiency
• To succeed in Walmart's fast-paced environment, candidates must possess a formidable academic foundation and the professional maturity to solve ambiguous problems with urgency. +

• Academic Foundation:

• A master's or PhD degree in a quantitative discipline—Computer Science, Statistics, Economics, Mathematics, or Operations Research—is required to navigate the mathematical complexities of Decision Sciences. +

• Professional Experience:

• You must bring 5+ years of experience in data science or operations research. While deep technical skill is mandatory, prior experience in retail or supply chain domains is highly preferred to provide the necessary context for complex operational workflows. +
• Technical Stack for

Scalability:

• Proficiency in Python and SQL is essential, framed through the lens of building scalable ML solutions. You must demonstrate the ability to transform ambiguous, real-world business problems into automated, measurable solutions that function within a massive production environment. +

• Communication & Strategic Storytelling:

• Data visualization is a core competency, not an add-on.

You must possess the ability to influence both technical peers and non-technical executives by translating complex model outputs into compelling narratives for change. While these core competencies are mandatory for daily execution, the Decision Sciences team prioritizes candidates who possess the vision to contribute to our future-state capabilities.

• Preferred Differentiators and Future-State Capabilities
• We seek candidates who look beyond the immediate task to enhance the broader analytical ecosystem, moving the team toward highly automated, agentic systems. +

• Platform & System Enhancement:

• Experience contributing to internal data science platforms, experimentation frameworks, or measurement systems. We value "platform thinking"—the transition from bespoke analyses to reusable tools that empower the entire organization. +

• Automation & Decision Support:

• Proven expertise in workflow automation and the development of scalable decision-support systems that reduce manual intervention for store leadership. +

• Emerging AI & Agentic Systems:

• Hands-on experience or significant exposure to AI agents, LLM-enabled workflows, and agent-based systems.

This expertise is a significant strategic advantage as we transition into next-generation AI applications for Store Operations. The ideal candidate is a unique blend of technical visionary and strategic influencer. Ready to operate with urgency and precision, the Staff Data Scientist is a high-impact leader poised to redefine the efficiency and effectiveness of Walmart US Store Operations through the power of Decision Science. ㅤ ㅤ ㅤ ㅤ ‎

• Minimum Qualifications...
• _Outlined below are the required minimum qualifications for this position.

If none are listed, there are no minimum qualifications._ Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field. Option 3: 6 years' experience in an analytics or related field

• Preferred Qualifications...
• _Outlined below are the optional preferred qualifications for this position.

If none are listed, there are no preferred qualifications._ 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, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture.

• Primary Location...
• 802 Respect Dr, Bentonville, AR 72716, United States of America Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job.

This policy applies to all employees and aims to create a safe and productive work environment.

Walmart, Inc. is an Equal Opportunity Employer

• By Choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. That means understanding, respecting, and valuing diversity
• unique styles, experiences, identities, abilities, ideas and opinions
• while being inclusive of all people.