Program Manager 2 – Supply Chain & Analytics Routing (hybrid - Seattle, Wa)

Nordstrom Nordstrom · Retail · Seattle, WA

Program Manager for Supply Chain & Analytics Routing at Nordstrom, focusing on data-driven improvements in ordering, fulfillment, and last-mile delivery. The role involves leading cross-functional initiatives, performing analytics with SQL and Python/R, developing data models, applying optimization techniques, and prototyping AI-enabled solutions for production deployment.

What you'd actually do

  1. Own and support end‑to‑end initiatives that improve ordering, fulfillment, and last‑mile routing performance
  2. Translate complex operational challenges into clear problem statements, execution plans, and measurable success criteria
  3. Define scope, milestones, timelines, and success metrics, and drive execution across highly cross‑functional teams
  4. Partner with stakeholders across Merchandising, Marketing, Digital Operations, Inventory, Store and Field Operations, Product, and Technology
  5. Communicate trade‑offs, risks, and recommendations clearly to enable informed decision‑making at multiple levels

Skills

Required

  • Bachelor’s degree in STEM, Supply Chain, Operations Research, or a related field
  • 5-7+ years of experience in supply chain, transportation, logistics, or e-commerce analytics and/or program management
  • Strong SQL and Python or R skills applied to large‑scale, complex datasets
  • Experience with data modeling, simulation, and exploratory analysis
  • Familiarity with predictive modeling and optimization techniques (LP/MILP, routing, network optimization)
  • Working knowledge of supply chain, last‑mile transportation, and/or parcel shipping operations
  • Experience partnering closely with engineering and technical teams in an agile development environment
  • Strong analytical and quantitative skills with a proven ability to use data and metrics to inform decisions
  • Ability to clearly communicate complex technical concepts to non‑technical, cross‑functional audiences
  • Demonstrated ability to influence without authority and collaborate across diverse teams
  • Comfort navigating ambiguity, independently defining problems, and driving solutions
  • Ability to manage multiple priorities in a fast‑paced environment
  • Strong written and verbal communication skills, with a focus on clarity and outcomes
  • Strong business acumen and a results‑oriented mindset

Nice to have

  • exposure to AI/ML frameworks such as PyTorch is a plus
  • Familiarity with cloud data platforms and/or business intelligence tools
  • Experience in retail or high‑volume e‑commerce logistics environments

What the JD emphasized

  • strong analytical depth
  • structured problem solving
  • comfortable operating independently in fast-paced, ambiguous environments
  • Strong SQL and Python or R skills applied to large‑scale, complex datasets
  • Experience with data modeling, simulation, and exploratory analysis
  • Familiarity with predictive modeling and optimization techniques (LP/MILP, routing, network optimization); exposure to AI/ML frameworks such as PyTorch is a plus
  • Working knowledge of supply chain, last‑mile transportation, and/or parcel shipping operations
  • Experience partnering closely with engineering and technical teams in an agile development environment
  • Strong analytical and quantitative skills with a proven ability to use data and metrics to inform decisions
  • Ability to clearly communicate complex technical concepts to non‑technical, cross‑functional audiences
  • Demonstrated ability to influence without authority and collaborate across diverse teams
  • Comfort navigating ambiguity, independently defining problems, and driving solutions
  • Ability to manage multiple priorities in a fast‑paced environment

Other signals

  • Develop data models, simulations, and exploratory analyses
  • Apply predictive modeling and optimization techniques
  • Prototype analytical and AI-enabled solutions
  • Partner with engineering teams to deploy them into production environments
  • Use metrics, experimentation, and test-and-learn approaches