Senior Credit Analytics Lead: Strategy & Risk

Walmart; Bentonville (AR); On-site; USD 90,000 - 180,000; Full time

Benefits offered by this job

Health benefits

401(k)

Paid time off (PTO)

Job summary

Walmart is seeking a Senior Manager, Advanced Analytics - Credit Strategy & Analytics to lead cross-functional efforts in designing credit strategies and analytics that balance growth with risk. The role partners with Product, Data Science, Seller Services, Billing, Finance, and Engineering to implement scalable controls and decisioning frameworks.

The team focuses on leveraging internal data and predictive signals to anticipate risks, optimize decisions, and strengthen the overall credit risk

Qualifications

• Bachelor's degree in Business, Finance, Accounting, Statistics, or related field and 4 years' experience in data analytics or related field OR 6 years'experience in data analytics or related field.

Responsibilities

• Lead development and execution of credit strategies, decisioning frameworks, and analytics for sustainable growth.
• Partner with Product, Data Science, Seller Services, Billing, Finance, and Engineering to design scalable risk controls.
• Develop credit limits, prepay strategies, reserves, and early warning capabilities.
• Leverage internal data and external signals to anticipate risks and inform decisions.
• Monitor portfolio performance and continuously refine risk management strategies.

Skills

Credit risk strategies

Cross-functional leadership

Predictive models

Data-driven decisions

Executive communication

Continuous improvement

Education

Bachelor's degree in Business/Finance/Statistics

Job description

Walmart is seeking a Senior Manager, Advanced Analytics - Credit Strategy & Analytics to lead cross-functional efforts in designing credit strategies and analytics that balance growth with risk. The role partners with Product, Data Science, Seller Services, Billing, Finance, and Engineering to implement scalable controls and decisioning frameworks.

The team focuses on leveraging internal data and predictive signals to anticipate risks, optimize decisions, and strengthen the overall credit risk