Senior Manager, Pricing Optimization, Old Navy

Gap Inc.•San Francisco, CA

About The Position

Gap Inc. is transforming how its brands use data and AI to make faster, more precise commercial decisions, and the Sr. Manager, Pricing Optimization plays a key role in that transformation. Pricing is one of the most direct levers a brand has to drive profitable growth — and in this role, you will be at the center of how Old Navy pulls it. The recommendations you develop and the insights you deliver will shape how the brand prices, promotes, and marks down product, with direct impact to margin performance and revenue outcomes. You will oversee the execution of pricing and promotional optimization for Old Navy, reviewing work developed by your team of analysts and ensuring every recommendation is grounded in accurate retail analytics, demand signal synthesis, and sensitivity analysis. You will be the analytical partner for Old Navy’s business owners and Finance partners —interpreting outputs from pricing agents, translating pricing signals into commercially actionable guidance, and synthesizing complex data into clear insight narratives for stakeholders. This is a people manager role: you will coach and develop a team of Pricing Optimization analysts, setting a high bar for analytical rigor, AI-informed decision making, and customer-centered commercial judgment.

Requirements

Bachelor’s degree required.
8+ years of experience in pricing analytics, demand planning, commercial analytics, or a related field—with direct exposure to retail or consumer products pricing.
2+ years of experience managing or leading teams, with a track record of developing analysts and influencing cross-functional stakeholders.
Hands-on proficiency in retail analytics, price elasticity modeling, sensitivity analysis and risk modeling, promotion effectiveness analysis, and markdown strategy.
Experience synthesizing demand signals and producing predictive insights and forecast interpretations that translate into commercial pricing recommendations.
Working knowledge of AI-scenario simulation and decision modeling tools; you can run, interpret, and quality-check AI-generated pricing scenarios, not just consume their outputs.
Proficiency with AI reporting and analytics platforms; you apply these tools fluently and coach others to do the same.
Demonstrated ability to translate complex commercial and financial data into clear, actionable recommendations for merchant and leadership audiences.

Nice To Haves

Strategically grounded and customer-centered: you evaluate pricing decisions not just through a financial lens, but through the lens of what is right for Old Navy’s customer—bringing critical thinking about customer impact into every recommendation.
AI-informed decision maker: you apply AI outputs with confidence and judgment, knowing when to trust the model, when to interrogate it, and when to escalate—and you model this mindset for your team.
Scenario-based storyteller: you make complex trade-offs legible to non-analytical stakeholders through clear framing, logical narrative, and well-structured commercial context.
AI-partnership mindset: you approach agentic tools and AI workflows as a collaborator—actively exploring how they augment analytical capacity while maintaining ethical oversight and brand alignment.
Experimentally minded: you build a culture of test-and-learn, identify high-value use cases for new approaches, and apply continuous learning to raise the team’s analytical bar over time.
Direct, collaborative, and commercially driven: you build trust with business owners, finance partners, and platform peers, communicate with candor, and follow through on commitments.

Responsibilities

Execute and review markdown and promotional analyses for Old Navy, applying retail analytics and sensitivity analysis to ensure recommendations optimize margin, conversion, and brand competitiveness.
Synthesize demand signals and predictive pricing insights to provide analytical input for seasonal and in-season decisions—including promotional effectiveness, markdown timing, yield management, and good/better/best pricing architecture.
Run and validate AI-scenario simulations and decision models, applying human judgment to outputs before they inform pricing actions—confirming assumptions, flagging risks, and maintaining brand and enterprise guardrails.
Interpret AI-generated pricing signals and translate them into commercially grounded recommendations, ensuring the “what” and the “so what” are always clear for merchant and finance partners.
Monitor in-season pricing actions and flag emerging risks or optimization opportunities, ensuring the brand can move with speed and confidence when market or inventory signals shift.
Articulate trade-offs clearly and confidently to Old Navy business owners and finance partners —using scenario-based storytelling to translate analytical complexity into decisions stakeholders can act on.
Support weekly and monthly business reviews with insight implication narratives: not just what the data shows, but what it means for pricing strategy, margin risk, and commercial opportunity.
Partner with the Pricing Performance Brand Lead to execute enterprise pricing strategy within Old Navy, applying consistent standards while accounting for brand-specific customer and inventory dynamics.
Collaborate with data science and technology partners to apply AI reporting tools and pricing platforms proficiently—operating as a skilled user and quality reviewer, not a passive recipient of outputs.
Manage and coach a team of Pricing Optimization analysts, setting clear expectations for analytical quality, AI-informed judgment, and commercial rigor across all work product.
Review associate deliverables with a structured eye—providing direct, constructive feedback that builds capability in demand signal interpretation, trade-off articulation, and insight communication.
Foster a team culture of experimentation and continuous learning: actively test new approaches, pilot AI tools, identify what works, and build on it systematically.
Help your team prioritize the highest-value pricing opportunities and use cases—developing their ability to distinguish signal from noise and focus effort where commercial impact is greatest.
Model ethical and brand-aligned judgment in every analytical decision—ensuring AI outputs are applied responsibly, with transparency about limitations and alignment with Old Navy’s brand values and customer commitments.