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# (USA) Senior Manager, Data Science (AI Technical Lead) - Next-Gen Customer Engagement & Returns

- **Company:** Wal-Mart Stores, Inc.
- **Location:** Bentonville, AR, United States
- **Experience:** Expert
- **Salary:** $110,000.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Adobe Analytics, Web Accessibility, Artificial Intelligence, Amazon Web Services, Data Analysis, Application Frameworks, Big Data, Cloud Computing, Code Review, Continuous Integration, Distributed Systems, Fault Tolerance, Python (Programming Language), Machine Learning, Natural Language Processing, Recommender Systems, Tensorflow, Scala (Programming Language), Software Engineering, SQL Databases, Web Content Accessibility Guidelines, Large Language Models, Apache Spark, Git, Pytest, Pyspark, Git Flow, Scikit Learn, Integration Tests, Kubernetes, Information Technology, Machine Learning Operations, Software Version Control, Docker
- **Published:** July 21, 2026
- **Apply:** https://www.disabledperson.com/jobs/73772683-usa-senior-manager-data-science-ai-technical-lead-next-gen-customer-engagement-returns

## About the Role

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
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Core Stack: Expert-level fluency in Python and SQL.
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Distributed Computing: Strong hands-on architecture experience with PySpark and handling massive, petabyte-scale datasets.
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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)
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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.
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Mentorship: A proven track record of upskilling technical teams, setting coding standards, and fostering a culture of continuous innovation.
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Education: Advanced degree (MS/PhD) in a quantitative field (Computer Science, Statistics, Operations Research, Economics, etc.)., 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.

## Description

models; you will architect the intelligent systems that redefine how we interact with our customers., 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.
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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.
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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.
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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.


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