Staff, Data Scientist

Walmart · Retail · Sunnyvale, CA

Staff Applied Scientist role at Walmart focused on enhancing the Spark Driver Platform using machine learning and reinforcement learning for pricing and incentive strategies. The role involves leading a team to design, train, evaluate, and deploy production models, with a focus on driving measurable business impact and improving driver experience and operational efficiency.

What you'd actually do

  1. Lead a team of applied scientists in developing innovative AI-driven solutions.
  2. Research and implement state-of-the-art machine learning techniques, including reinforcement learning and deep learning.
  3. Collaborate cross-functionally with business, product, and engineering stakeholders to ensure AI solutions align with Walmart’s strategic objectives.
  4. Design and optimize machine learning pipelines to ensure scalability, efficiency, and real-time processing capabilities.
  5. Build and deploy end-to-end models, balancing accuracy, computational efficiency, and measurable business impact.

Skills

Required

  • Ph.D. or equivalent advanced degree in Computer Science, Statistics, Operations Research, Economics, or a related field.
  • Extensive experience in machine learning, reinforcement learning, GenAI, and Agentic AI.
  • 5+ Years of experience of deploying ML models in production, preferably in high-scale environments.
  • Strong programming skills in Python, Java, C, or C++.
  • Experience with large-scale data systems (Spark/Hive) and cloud computing (GCP/Azure).
  • Demonstrated ability to drive projects from conception to production in a fast-paced, dynamic environment.
  • Excellent communication and leadership skills, with the ability to influence and inspire cross-functional teams.

What the JD emphasized

  • leading a team of Applied Scientist to design, train, evaluate, deploy, and monitor production models
  • driving measurable business impact
  • 5+ Years of experience of deploying ML models in production, preferably in high-scale environments

Other signals

  • reinforcement learning
  • pricing and incentive
  • Capacity Optimization
  • Driver Search
  • Driver Matching
  • Driver Offer Pricing
  • Driver Surge Pricing
  • Incentive Strategy
  • Routing Optimization
  • ETA Prediction
  • Trust Safety