Senior, Data Scientist - Workforce Intelligence

Walmart Walmart · Retail · Bentonville, AR

Senior Data Scientist role focused on building and improving labor forecasting capabilities for Walmart using ML/AI and GenAI. The role involves developing new forecasting models, enhancing existing ones, and building a scalable platform for automation across the model lifecycle, including data, evaluation, and deployment. It requires strong technical skills in SQL, Python, ML/AI, and GenAI experience is preferred.

What you'd actually do

  1. Partner cross functionally across Store Operation, Supply Chain, Transportation and Workforce Intelligence team to understand the current business and future scope and translate them into labor forecasting strategy
  2. Work with the forecasting team to develop new forecasting capabilities to support the aligned broader labor strategy
  3. Improve the accuracy and robustness of the end-to-end forecasting suite through innovative modeling approaches and optimization techniques
  4. Leverage GenAI and ML/AI algorithms to help build a scalable platform that supports automation across the model lifecycle (runs, evaluation, data validation, drift monitoring, and deployment).
  5. Work with partner teams (e.g., Labor Generation, Industrial Engineering) to identify process gaps and develop data science solutions that improve business outcomes.

Skills

Required

  • SQL
  • Python
  • ML/AI
  • Statistics
  • Master's degree in a relevant field (Business Analytics, Data Science, Statistics, Software Engineering, ML Engineering, Computer Science)
  • 3+ years’ experience in building and delivering real life data science products

Nice to have

  • GenAI hands-on experience
  • Workforce/Store Ops experience
  • retail or supply chain environments experience

What the JD emphasized

  • machine learning, advanced analytics and statistics, GenAI, and deep operational and financial data to predict labor demand with high precision
  • GenAI
  • ML/AI
  • GenAI hands-on experience preferred

Other signals

  • Leverage GenAI and ML/AI algorithms to help build a scalable platform that supports automation across the model lifecycle (runs, evaluation, data validation, drift monitoring, and deployment).
  • develop new forecasting capabilities
  • Improve the accuracy and robustness of the end-to-end forecasting suite through innovative modeling approaches and optimization techniques