Gap Inc. Manager, Pricing Optimization, Navy

About Gap Inc.

At Gap Inc., we create culture as much as we create clothes. Our ambition is to become a high-performing house of iconic American brands that shape culture. Our portfolio includes Old Navy, Gap, Banana Republic, and Athleta, each bringing a distinct point of view to how we show up in the world and serve our customers. Old Navy democratizes style with quality and value for all.

Gap champions originality through essential pieces that celebrate individuality. Banana Republic is rooted in a spirit of discovery, creating modern pieces inspired by craftsmanship and travel. Athleta champions the Power of She through confidence, strength, and movement. We're driven by a shared purpose to bridge gaps between people, perspectives, and possibilities to create a better world.

Gap Inc. is transforming how its brands use data and AI to make faster, more precise commercial decisions. The Manager, Pricing Optimization is the engine of Old Navy's pricing function—the person who runs models, builds scenarios, synthesizes demand signals, and produces decision-ready analysis that drives how the brand promotes and marks down product. Reporting to the Sr. Manager, Pricing Optimization, you will own the execution of specific pricing and promotional analytics work streams, operating with a high degree of technical proficiency and analytical independence.

You will apply and validate outputs from pricing agents, build and stress-test scenario models, and distill complex data into clear, well-packaged insights for business owners and finance partners. You will also support the development of pricing analysts and help train pricing agents, playing a key part in building the team's analytical capabilities as the function grows.

Build and Execute Pricing Optimization

• Own specific markdown and promotional analytics work streams for Old Navy—build and run models, apply elasticity and sensitivity analysis, and produce well-structured recommendations grounded in accurate retail data.
• Develop and stress-test AI-scenario simulations for in‑season and seasonal pricing decisions, validating outputs from pricing agents and flagging assumptions, inconsistencies, or risks before final recommendations.
• Synthesize demand signals and apply predictive pricing insights across assigned categories—including promotional effectiveness, markdown timing, yield management, and good/better/best architecture—to produce accurate, thorough, commercially grounded analysis.
• Maintain ongoing monitoring of in‑season pricing actions, proactively identifying risks or optimization opportunities and escalating with clear data and a recommended point of view.
• Apply AI reporting tools and pricing platforms as a proficient daily user—interrogating outputs critically, ensuring data integrity, and knowing when something requires human review before informing a decision.

Prepare Decision‑Ready Analysis and Insights

• Package analytical work into clear, well‑structured deliverables for business owners and finance partners—making the “what” and “so what” explicit and trade‑offs easy to act on.
• Prepare supporting analysis and materials for weekly and monthly business reviews, synthesizing pricing performance across assigned categories into accurate, insight‑led summaries.
• Translate data complexity into plain commercial framing: articulate what it means for margin, revenue, or promotional ROI in language that non‑analytical stakeholders can use.
• Respond to ad hoc analytical requests from Pricing leaders with speed and accuracy, delivering clean, well‑reasoned work under time pressure.

Help Build the Future of Pricing

• Contribute directly to training and refining Old Navy’s pricing agents—identify where AI outputs fall short, document patterns, and work with data science and technology partners to improve model performance over time.
• Help define what good looks like in an agentic pricing workflow—document analytical standards, flag edge cases, and contribute institutional knowledge that shapes how pricing agents are structured, validated, and improved.
• Bring a builder’s mindset to a function that is being created from scratch—pilot new…