Senior Manager, Data Science

Retail AI Foundations is part of the Retail Intelligence group within Walmart's AI & Data organization. The team develops and deploys Generative AI and machine learning platforms, models, and services across Walmart's highest-impact growth pillars—including AI Shopping, Social Commerce, Walmart Connect advertising, creator experiences, marketing, and rich-media content.

Our Applied Science and ML Engineering teams build AI capabilities across Large Language Models (LLMs), image and video generation, and multimodal understanding. We partner with talented scientists, engineers, product managers, and business leaders to improve experiences for customers, associates, advertisers, and creators, while delivering measurable business outcomes. We are committed to exceeding industry standards through cutting-edge research, strong engineering execution, and responsible AI practices.

The Senior Manager, Data Science will lead an Applied Science and ML Engineering team within Retail AI Foundations. This leader will set the scientific and technical direction for production AI systems, working backward from customer needs and business priorities to define the problems, success measures, and investments that matter most.

• Lead, mentor, and grow a high-performing team of Applied Scientists and ML Engineers.
• Define the technical roadmap and science investment strategy for LLMs, image and video generation, multimodal understanding, agentic simulation, and multi-agent systems.
• Translate priority business opportunities and customer‑experience needs into AI product strategy, technical priorities, and measurable outcomes.
• Lead the end-to-end development of ML and GenAI capabilities, including data strategy, experimentation, model development, evaluation, deployment, and iteration.
• Partner across product, engineering, data, and business teams to deliver solutions for AI Shopping, Social Commerce, Walmart Connect, creator experiences, marketing, and rich-media content.
• Establish standards for model quality, safety, reliability, latency, scalability, and responsible AI.
• Guide architecture and model decisions spanning proprietary and open-weight models, post-training, fine-tuning, retrieval, and agentic workflows.
• Communicate strategy, technical tradeoffs, model performance, and business impact to senior leaders and cross-functional stakeholders.

• Strong expertise in machine learning, deep learning, NLP, information retrieval, analytics, and model evaluation.
• Experience delivering complex ML systems, particularly across Generative AI, computer vision, multimodal AI, or deep learning.
• Ability to turn customer and business needs into clear technical requirements, model designs, and scalable production solutions.
• Strong cross-functional communication skills, including the ability to align product, engineering, technical teams, and leadership.
• Experience with distributed training and inference frameworks, large-scale model serving, and massively parallel GPU systems.

• 2+ years of people‑management experience leading Applied Scientists, Data Scientists, or ML Engineers, and 7+ years of experience building machine learning models or algorithms for business applications.
• Master’s or PhD in Computer Science, Electrical Engineering, Machine Learning, Engineering, Robotics, Operations Research, Statistics, Mathematics, or a related quantitative field; or equivalent practical experience.
• Experience with LLM post-training and alignment, including supervised fine-tuning, reinforcement learning, RLHF, DPO, or related techniques.
• Experience with image or video generation models, multimodal understanding models, or production…