Group Director, Data Science - Decision Science, Merchandising
Walmart
Sales & Business Development, Data Science
USD 195k-370k / year + Equity
Posted on Mar 24, 2026
Position Summary...
About Decision Sciences at Walmart:Walmart moves with speed at scale. Doing that well requires more than good instincts or dashboards—it requires clear, defensible decisions embedded directly into how the business operates.
Decision Sciences is a newly formed organization within Walmart U.S. with a focused mandate: ensure decision makers know what is actually moving the business and why, and translate that insight into clear investment guidance that changes where Walmart deploys capital, engineering capacity, time, and organizational attention.
Decision Sciences partners directly with senior business leaders to move beyond descriptive analytics and into causal understanding, prioritized action, and faster execution, while maintaining or improving service levels across existing analytics and science teams.
The Group Director, Decision Sciences - Merchandising is a senior leadership role responsible for standing up and leading the new Decision Sciences team, supporting the Merchandising organization.
This role sits at the intersection of business strategy, advanced analytics, experimentation, and talent leadership. The Group Director is accountable not just for analysis quality, but for whether the work changes decisions.
This is an enterprise shaping role, operating with VP level partners and leading teams that influence some of Walmart’s highest leverage decisions.
What you'll do...
Lead Decision Science at the Business Frontier- Own Decision Sciences engagement for one or more major business domains (e.g., eCommerce, Marketplace, Marketing, Stores, Supply Chain).
- Partner directly with senior leaders to clarify outcomes, frame the right questions, and identify where science can most meaningfully direct investment.
- Ensure all work is explicitly tied to Customer Value Proposition priorities (Price, Assortment, Experience, Trust) and WM U.S. leadership AOP commitments.
- Move teams beyond reporting and descriptive analytics into causal inference, experimentation, and decision guidance.
- Ensure outputs produce directional clarity—what to invest in more, what to deprioritize, and where intuition is wrong.
- Hold a high bar: work must change investment allocation, narrow focus, or contradict prevailing assumptions to be considered successful.
- Ensure experiments and tests that reach senior leadership meet Decision Sciences standards for rigor, validity, and interpretability.
- Partner with shared experiment platforms and methodologies to maintain consistency and trust across the enterprise.
- Lead, coach, and grow senior data scientists, applied scientists, and analytics leaders.
- Build teams that are fluent in both business context and scientific method, capable of operating as trusted advisors rather than back‑office analysts.
- Set clear expectations around outcomes, prioritization, and time‑to‑value.
- Run a front‑office pod tightly aligned to business leaders, owning the relationship and outcomes.
- Leverage back‑office shared capabilities (foundational data, tooling, causal frameworks, experimentation standards) to reduce duplication and increase leverage.
- Contribute to raising the enterprise “floor” for decision quality through shared standards, training, and review.
- Maintain a clear project hopper and capacity plan.
- Say “no” or “not yet” when work does not meet the Decision Sciences bar for leverage.
- Balance speed with rigor, and ambition with execution reality.
- Senior leaders can clearly point to moments where Decision Sciences changed what Walmart invested in or how it executed.
- Teams deliver fewer, higher‑impact analyses rather than broad, diluted coverage.
- Decision velocity improves without sacrificing quality.
- Trust in scientific outputs increases across leadership forums.
- The team is energized, focused, and operating with a shared identity and standards.
- Deep experience leading data science, applied analytics, or economics teams in complex, scaled environments.
- Proven ability to translate advanced analysis into executive‑level decisions and action.
- Strong grounding in experimentation, causal inference, and decision science—not just metrics and dashboards.
- Experience partnering directly with senior business leaders on high‑stakes decisions.
- Operates comfortably at executive level with credibility and influence.
- Balances strategic thinking with operational execution.
- Willing to challenge intuition and surface uncomfortable truths with clarity and respect.
- Passionate about building teams and raising standards, not just delivering individual insights.
- Obsessed with impact over activity.
- Comfortable narrowing focus rather than expanding scope.
- Energized by ambiguity and complex systems.
- Motivated by shaping how a Fortune‑scale company makes decisions.
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.
The annual salary range for this position is $195,000.00 - $370,000.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include :
- Stock
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Minimum Qualifications...
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 8 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 6 years' experience in an analytics related field. Option 3: 10 years' experience in an analytics or related field.4 years' supervisory experience.
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, Supervisory, 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.

















