WHO YOU’LL WORK WITH

You will be part of Nike’s Demand Planning and Pricing technology Team, building capabilities that enable Demand planning, Assortment Planning, Merchandise Financial Planning, Pricing & Promotions related data platforms. You will partner with Engineering, Data, Product, and Business teams across global supply chain domains, working closely with Store Athletes, Planning Functions, Advanced Analytics and Platform teams to deliver scalable, high-impact solutions.

WHO WE ARE LOOKING FOR

Nike is seeking a Lead Technical Product Manager with strong product leadership, technical depth and deep Planning and Pricing domain knowledge. The role is focused on optimizing how Nike plans demand and assortment, manages pricing and promotions, and improves decision-making across planning and pricing workflows to better serve Nike's consumers. This individual operates at the intersection of business, technology and operations, leading product strategy, roadmap, execution, cross functional alignment and measurable business outcomes across global teams. 

The ideal candidate brings strong ownership, systems thinking, data-driven decision-making, and the ability to translate business needs into scalable technical solutions. They can independently lead product lifecycle execution from discovery through delivery, operate in ambiguity, influence senior stakeholders, manage dependencies, and ensure solutions deliver measurable value aligned to cost optimization, reliability, operational efficiency and scale. 

• 10+ years of experience delivering medium to large-scale products in cross-functional environments. 

• 7+ years of experience working in Planning and Pricing domains, preferably across demand planning, assortment planning, pricing, promotions, optimization or analytics-led planning capabilities. 

• Demonstrated experience building, adopting or leveraging AI agents, AI-assisted workflows, automation or optimization capabilities to improve efficiency, planning quality, pricing decisions, backlog maturity or operational outcomes. 

• Proven experience leading product lifecycle from discovery to delivery with minimal oversight. 

• Product champion with strong interpersonal and influencing skills to engage business stakeholders across geographies, shape roadmaps and improve operational outcomes. 

• Strong technical fluency across APIs, data models, distributed systems, system design, platform architecture, AI-enabled product patterns and data platform concepts. 

• Experience influencing senior stakeholders, leading large-scale cross-functional initiatives across geographies and aligning cross-functional teams. 

• Bachelor's degree or equivalent combination of education and experience. Engineering or technology background preferred. 

WHAT YOU’LL WORK ON

You will define and lead product strategy and execution for supply chain data and platform capabilities, enabling scalable, reliable and cost-optimized operations across Nike's Demand Planning and Pricing ecosystem.

• Define, own and execute product vision, roadmap and strategies aligned to business goals and Demand Planning and Pricing platform priorities across cost, reliability, scale and consumer impact.

• Lead cross-functional squads through the full product lifecycle from discovery to delivery, ensuring outcomes are value-driven and measurable.

• Translate planning and pricing business needs into prioritized roadmaps, capabilities, user stories and decision-support outcomes.

• Partner with engineering, architecture, data, analytics and business teams on technical decisions, integration design, architecture, dependency management and delivery sequencing.

• Drive stakeholder alignment across planning, pricing, promotions, analytics and platform teams.

• Support integration of systems and data products across planning and pricing domains, with a focus on quality, reliability, adoption and downstream consumption.

• Identify and scale AI agent use cases that improve optimization, efficiency, discovery, backlog shaping, business requirements, decision intelligence or operational workflows.

• Monitor product performance, define success metrics, track adoption and use data to drive continuous improvement.

• Elevate product management maturity through best practices, frameworks, mentoring and reusable AI-enabled product practices.

• AI practice leadership: model effective AI use for backlog shaping, BRDs, discovery artifacts, impact analysis and product decision support; share prompts, checklists and review norms that help squads move faster without sacrificing quality.