(USA) Senior Manager, Data Science - AI Strategy (Spark Earnings Excellence)

Walmart•Bentonville, AR

2d•$110,000 - $220,000

About The Position

The Senior Manager, Data Science - AI Strategy for Spark Earnings Excellence owns and drives the team’s AI and automation strategy. The role identifies high-impact opportunities to automate manual work and apply AI and machine learning to earnings analysis, then partners with business and technology teams to deliver solutions. It serves as a strategic bridge between business users and technology teams and is accountable for embedding AI across the team’s work. The Spark Earnings Excellence team ensures the accuracy, integrity, and quality of driver earnings each week. It develops an AI-first operating model across its pillars, applying advanced data science and machine learning in close collaboration with business partners to improve outcomes for drivers and Walmart. The role sets a multi-year AI and automation vision, establishes scalable data, platform, and governance foundations, and delivers agentic AI applications. It leads cross-functional teams from concept through production, prioritizes initiatives using business cases, promotes responsible AI practices, and communicates results to executive leaders. The position is based at the listed Walmart location in Bentonville, Arkansas.

Requirements

8+ years in data science, analytics, or machine learning, including 3+ years leading high-performing teams.
Proven record of shipping machine learning and Generative AI solutions with measurable business impact.
Deep expertise in statistical modeling, machine learning, anomaly detection, and experimentation.
Hands-on experience with Python, SQL, and machine learning frameworks.
Experience building Generative AI and agentic AI systems from prototype to production.
Experience with model evaluation, including evaluation design, drift monitoring, benchmarking, and observability.
Knowledge of data governance, controls, audits, sensitive data, and AI cost optimization.
Ability to translate ambiguous business problems into technical requirements and partner with engineering teams.
Ability to communicate complex models clearly to executives and non-technical audiences.
Meet one of the stated minimum qualification pathways: bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or a related field plus 5 years of analytics-related experience; master's degree in one of those fields or a related field plus 3 years of analytics-related experience; or 7 years of experience in an analytics or related field.

Nice To Haves

Master’s degree or equivalent in a quantitative field.
Finance or Compliance experience.
Data science, machine learning, or optimization models experience.
PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, or Econometrics.
Successful completion of one or more assessments in Python, Spark, Scala, or R.
Supervisory experience.
Experience using open-source frameworks such as scikit-learn, TensorFlow, or Torch.
Background creating inclusive digital experiences, including knowledge of WCAG 2.2 AA standards, assistive technologies, and digital accessibility best practices.

Responsibilities

Set and own the multi-year AI and automation vision across Spark Earnings Excellence pillars.
Architect scalable data, platform, and governance foundations to enable AI at enterprise scale.
Deliver agentic AI use cases such as payment validation, defect root-cause analysis, reconciliation, anomaly detection, and audit reporting.
Prioritize the portfolio using rigorous business cases that balance impact, effort, and risk.
Lead cross-functional Engineering, Data Science, and platform teams from concept through production, with measurable outcomes.
Partner with Legal, Compliance, and InfoSec on responsible AI, including evaluations and drift monitoring.
Scale AI fluency and change management, and communicate impact to executive leadership.
Identify opportunities to automate manual work and apply AI/ML to earnings analysis, partnering with business and technology teams to deliver solutions.
Embed AI across the Spark Earnings Excellence team's work.

Benefits

Competitive pay and performance-based bonus awards.
Medical, vision, and dental coverage.
401(k).
Stock purchase.
Company-paid life insurance.
Paid time off, including sick leave, parental leave, family care leave, bereavement leave, jury duty leave, and voting leave.
Short-term and long-term disability.
Company discounts.
Military Leave Pay.
Adoption and surrogacy expense reimbursement.
PTO and/or PPTO usable for vacation, sick leave, holidays, or other purposes.
Live Better U education benefit program, with tuition, books, and fees paid for eligible programs.