(USA) Senior Manager, Data Science

Walmart•Sunnyvale, CA

About The Position

Retail AI Foundations, part of Walmart’s Retail Intelligence group within the AI & Data organization, develops and deploys Generative AI and machine learning platforms, models, and services across Walmart growth areas, including AI Shopping, Social Commerce, Walmart Connect advertising, creator experiences, marketing, and rich-media content. Applied Science and ML Engineering teams build capabilities in large language models (LLMs), image and video generation, and multimodal understanding, partnering with scientists, engineers, product managers, and business leaders to improve experiences and deliver measurable business outcomes while applying responsible AI practices. The Senior Manager, Data Science leads an Applied Science and ML Engineering team and sets the scientific and technical direction for production AI systems. The role works backward from customer needs and business priorities to define important problems, success measures, and investments. It includes establishing technical roadmaps and science investment strategy, leading end-to-end development of ML and GenAI capabilities, and delivering scalable solutions with cross-functional partners.

Requirements

  • Strong expertise in machine learning, deep learning, NLP, information retrieval, analytics, and model evaluation.
  • Experience delivering complex ML systems, particularly in Generative AI, computer vision, multimodal AI, or deep learning.
  • Ability to translate customer and business needs into technical requirements, model designs, and scalable production solutions.
  • Strong cross-functional communication skills and 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.
  • Minimum qualification options: bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or a related field and 5 years of experience in an analytics-related field; or master’s degree in one of those fields and 3 years of related experience; or 7 years of experience in an analytics or related field.

Nice To Haves

  • At least 2 years of people-management experience leading Applied Scientists, Data Scientists, or ML Engineers.
  • At least 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 computer-vision systems.
  • Experience in data science, machine learning, or optimization models.
  • 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.
  • Knowledge of WCAG 2.2 AA standards, assistive technologies, and digital accessibility best practices.

Responsibilities

  • 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 business opportunities and customer-experience needs into AI product strategy, technical priorities, and measurable outcomes.
  • Lead end-to-end development of ML and Generative AI capabilities, including data strategy, experimentation, model development, evaluation, deployment, and iteration.
  • Partner with 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 involving 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.

Benefits

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