Position Summary...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.
What you'll do...- Architect Autonomous AI Systems: Design the end-to-end algorithmic framework for our proactive returns intelligence agent. You will fuse Causal Inference, Deep Learning, and Large Language Models (LLMs) to analyze structured transaction data alongside unstructured customer feedback, chat logs, and product reviews.
- Lead the Transition from Insight to Action: Spearhead the application of Causal AI to understand the "why" behind return behaviors. You will move the team beyond simple correlation to answer counterfactuals (e.g., "If we offer a 15% discount right now, will it save the sale and the customer relationship?").
- Drive Engineering Excellence: Act as the ultimate gatekeeper for the AI codebase. You will mentor a team of brilliant Data Scientists, elevating their engineering maturity from local "notebook scripts" to scalable, modular, and deployable production packages. You will enforce strict version control (Git), conduct rigorous code reviews, and mandate comprehensive unit/integration testing.
- Pioneer ML & GenAI Observability: The real world is chaotic. You will design state-of-the-art MLOps and monitoring frameworks to track real-time model performance, data drift, and LLM hallucination rates. You ensure our AI agents adapt dynamically as consumer trends and macroeconomic factors shift.
- Strategic Technical Leadership: Translate highly ambiguous business objectives ("Reduce omni-channel friction") into concrete, executable AI roadmaps. You will bridge the gap between complex algorithmic concepts and executive business strategy.
- Hands-On Innovation: Roll up your sleeves. You will write high-performance, fault-tolerant Python and PySpark code for the most complex, mission-critical components of our recommendation engines.
What you'll bring:The Tech Stack & Expertise, AI, Machine Learning & Analytics- Advanced Modeling: Deep expertise in time-series forecasting, anomaly detection, and modern predictive modeling.
- Causal Inference & Experimentation: 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.
- NLP & GenAI: Experience leveraging Natural Language Processing and LLMs to extract sentiment and actionable features from unstructured customer engagement data.
Software Engineering & Big Data Architecture - Core Stack: Expert-level fluency in Python and SQL.
- Distributed Computing: Strong hands-on architecture experience with PySpark and handling massive, petabyte-scale datasets.
- Engineering Rigor: You don't merge code without tests. Extensive experience with Unit/Integration Testing (pytest) and advanced Git management (branching strategies, CI/CD pipeline integration, conflict resolution).
Leadership & MLOps (Preferred Qualifications) - Model Deployment: Experience with Docker/Kubernetes for containerized model serving, and familiarity with cloud infrastructure (GCP, or AWS) to optimize compute resources for heavy AI workloads.
- Mentorship: A proven track record of upskilling technical teams, setting coding standards, and fostering a culture of continuous innovation.
- Education: Advanced degree (MS/PhD) in a quantitative field (Computer Science, Statistics, Operations Research, Economics, etc.).
The above information has been designed to indicate the general nature and level of work performed in the role. It is not designed to contain or be interpreted as a comprehensive inventory of all responsibilities and qualifications required of employees assigned to this job. The full Job Description can be made available as part of the hiring process.
Minimum Qualifications...Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field.
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 experience, 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.
Primary Location...805 Respect, Bentonville, AR 72716, United States of America
