About The Position

The Customer Engagement Services team is building an autonomous, intelligent ecosystem that doesn't just process returns; it predicts, personalizes, and prevents friction. We are moving beyond reactive dashboards to deploy Agentic AI and Causal Machine Learning systems capable of digesting multi-modal data, diagnosing root causes of customer pain points, and triggering real-time, personalized interventions. We are seeking a Senior Manager, Data Science to serve as the Technical Lead and visionary for this initiative. You are a high-impact player-coach who thrives at the bleeding edge of AI but demands rigorous software engineering standards. You won't just build models; you will architect the intelligent systems that redefine how we interact with our customers.

Requirements

  • Deep expertise in time-series forecasting, anomaly detection, and modern predictive modeling.
  • Proven ability to apply causal frameworks (e.g., Do-calculus, causal impact, propensity matching) to observational data to isolate exact friction points in the return journey.
  • Experience leveraging Natural Language Processing and LLMs to extract sentiment and actionable features from unstructured customer engagement data.
  • Expert-level fluency in Python and SQL.
  • Strong hands-on architecture experience with PySpark and handling massive, petabyte-scale datasets.
  • Extensive experience with Unit/Integration Testing (pytest) and advanced Git management (branching strategies, CI/CD pipeline integration, conflict resolution).
  • Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field.
  • OR Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field.
  • OR 7 years' experience in an analytics or related field.

Nice To Haves

  • Experience with Docker/Kubernetes for containerized model serving.
  • Familiarity with cloud infrastructure (GCP, or AWS) to optimize compute resources for heavy AI workloads.
  • A proven track record of upskilling technical teams, setting coding standards, and fostering a culture of continuous innovation.
  • Advanced degree (MS/PhD) in a quantitative field (Computer Science, Statistics, Operations Research, Economics, etc.).
  • 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 experience.
  • Using open source frameworks (for example, scikit learn, tensorflow, torch).
  • 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.
  • Knowledge of accessibility best practices and joining to continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture.

Responsibilities

  • Design the end-to-end algorithmic framework for our proactive returns intelligence agent, fusing Causal Inference, Deep Learning, and Large Language Models (LLMs) to analyze structured transaction data alongside unstructured customer feedback, chat logs, and product reviews.
  • Spearhead the application of Causal AI to understand the "why" behind return behaviors, moving the team beyond simple correlation to answer counterfactuals.
  • Act as the ultimate gatekeeper for the AI codebase, mentoring a team of Data Scientists to elevate their engineering maturity from local "notebook scripts" to scalable, modular, and deployable production packages.
  • Enforce strict version control (Git), conduct rigorous code reviews, and mandate comprehensive unit/integration testing.
  • Design state-of-the-art MLOps and monitoring frameworks to track real-time model performance, data drift, and LLM hallucination rates, ensuring AI agents adapt dynamically.
  • Translate highly ambiguous business objectives into concrete, executable AI roadmaps, bridging the gap between complex algorithmic concepts and executive business strategy.
  • Write high-performance, fault-tolerant Python and PySpark code for the most complex, mission-critical components of our recommendation engines.

Benefits

  • Competitive pay
  • Performance-based bonus awards
  • Medical coverage
  • Vision coverage
  • Dental coverage
  • 401(k)
  • Stock purchase
  • Company-paid life insurance
  • PTO (including sick leave)
  • Parental leave
  • Family care leave
  • Bereavement
  • Jury duty
  • Voting leave
  • Short-term disability
  • Long-term disability
  • Company discounts
  • Military Leave Pay
  • Adoption and surrogacy expense reimbursement
  • PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes.
  • Walmart-paid education benefit program (Live Better U) for full-time and part-time associates, covering high school completion to bachelor's degrees, including English Language Learning and short-form certificates. Tuition, books, and fees are completely paid for by Walmart.
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