Senior Manager, Data Analytics; Supplier Finance Data Strategy

Senior Manager, Data Analytics (Supplier Finance Data Strategy)

Bentonville, AR, 703 Associate Dr, Bentonville, AR

R-2481309 | $90,000 - $180,000/yr | Regular/Permanent

Walmart is seeking a strategic and results-driven Senior Manager, Data Analytics (Supplier Finance Data Strategy) to unlock the full potential of our data ecosystem and accelerate supplier financing programs. This role sits at the intersection of finance, data, and technology—transforming complex datasets into scalable, insight‑driven solutions that power growth and innovation. You will shape how data is sourced, structured, and activated across the enterprise while influencing high‑impact financial decisions.

This is a unique opportunity to build next‑generation data products and AI‑enabled analytics that enhance supplier experiences and drive measurable business outcomes.

The team is focused on expanding access to working capital solutions for Walmart’s supplier ecosystem, enabling growth, stability, and stronger partnerships. The team operates cross‑functionally, collaborating closely with merchandising, supply chain, accounts payable, technology, and external financial partners. Data and analytics are central to how the team designs, scales, and optimizes financing programs. This role plays a critical part in connecting data strategy to execution, ensuring the team can deliver innovative, efficient, and supplier‑centric financial solutions.

• Lead the data strategy for supplier finance initiatives, identifying and activating key data sources to enable scalable program growth.
• Partner cross‑functionally with technology, merchandising, accounts payable, and supply chain teams to define data requirements and priorities.
• Assess and improve data quality, integrity, and completeness across multiple enterprise systems.
• Design and build data models and analytics frameworks supporting trade flows, invoicing, and payment cycles.
• Apply financial and lending principles to inform credit assessments, underwriting inputs, and risk‑based decisioning.
• Translate complex datasets into actionable insights that guide program design, supplier segmentation, and strategy.
• Evaluate and integrate external data sources (e.g., credit data, market data) to enhance analytics and fill internal data gaps.
• Collaborate with external partners (banks, fintechs, underwriters) to optimize data sharing and support lending decisions.
• Leverage advanced analytics, AI/ML, and automation to improve forecasting accuracy, scalability, and operational efficiency.

• Bachelor’s degree in Finance, Accounting, Economics, Data Analytics, or a related field.
• 8+ years of experience in data analytics, finance, treasury, or related areas with a strong data‑driven focus.
• Strong financial acumen, including knowledge of lending principles, credit risk, and working capital dynamics.
• Experience with retail and financial processes such as order management, invoicing, and payment workflows.
• Proven ability to assess and manage data quality across complex, interconnected systems.
• Demonstrated success influencing cross‑functional stakeholders across business and technology teams.
• Hands‑on experience building data models, analytics solutions, or data products with measurable impact.
• Proficiency in tools such as SQL, Python, Power BI, Tableau, or similar analytics platforms.
• Familiarity with enterprise systems (e.g., SAP) and experience applying AI/ML or automation to analytics workflows.

• Option 1:
  Bachelor’s degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Arts, Finance or related field and 4 years’ experience in data analysis, data science, statistics, or related field.
• Option 2:
  Master’s degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years’ experience in data analysis, data science, statistics, or related field.
• Option 3: 6 years’ experience in data analysis, data science, statistics, or related field.
• 1 year’s supervisory experience.

• Data science, data analysis, statistics, or…