Director, Data Science, Network Design - International Supply Chain

Walmart Walmart · Retail · Bentonville, AR

Lead the data science and optimization engine behind International Supply Chain network design. This role involves translating complex supply chain questions into scalable analytical solutions using optimization, simulation, and ML frameworks, with a focus on improving delivery speed, cost-to-serve, and network performance. The role also includes defining data needs, validating and deploying models, and leading data science talent.

What you'd actually do

  1. Translate network design and capacity questions into optimization, simulation, and ML frameworks.
  2. Build, validate, and deploy models that quantify tradeoffs, ROI, and performance impacts.
  3. Define data needs, assess sources, and set quality standards for modeling inputs.
  4. Deliver executive storytelling and visualizations that drive alignment and decisions.
  5. Lead and mentor data science talent; establish analytics and modeling best practices.

Skills

Required

  • Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field.
  • Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field.
  • 8 years' experience in an analytics or related field

Nice to have

  • 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)
  • knowledge of accessibility best practices

What the JD emphasized

  • Deep experience applying optimization, simulation, and/or machine learning to supply chain decisions.
  • Proven ability to frame ambiguous business problems into measurable analytical deliverables.
  • Strong model validation, documentation, and production deployment/lifecycle management discipline.

Other signals

  • Translate network design and capacity questions into optimization, simulation, and ML frameworks.
  • Build, validate, and deploy models that quantify tradeoffs, ROI, and performance impacts.
  • Define data needs, assess sources, and set quality standards for modeling inputs.