Sr. Analyst 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 Senior Analyst, Pricing Optimization is where that analytical work gets executed. This role is the analytical foundation of Old Navy’s pricing function—the person who runs the day-to-day models, prepares the data, validates outputs from pricing agents, and ensures the team has accurate, well-structured analysis ready to inform every pricing and promotional decision. Reporting to the Manager, Pricing Optimization, you will support the execution of specific pricing and promotional analytics work streams—preparing data, running models, and applying rigorous quality checks to outputs from pricing agents. You will produce clean, accurate analysis that your manager and team bring to Old Navy’s business owners and finance partners. This is an individual contributor role designed for someone who is analytically precise, eager to build their skills in an AI-enabled pricing environment, and ready to be a foundational contributor to a function being built from scratch.

Requirements

Bachelor’s degree required.
1-4 years of experience in pricing analytics, demand planning, merchandise planning, commercial analytics, or a related field—including internship or co-op experience in retail or consumer products.
Foundational analytical skills and a strong desire to build proficiency in pricing model execution: data preparation, elasticity inputs, sensitivity analysis, promotional effectiveness, and scenario modeling.
Experience or an aptitude for working with AI-generated analytical outputs: you are comfortable applying, reviewing, and quality-checking outputs from pricing agents, and you understand the importance of human oversight before outputs inform decisions.
Comfort with reporting and analytics platforms; you learn tools quickly, apply them in your day-to-day analytical work, and are motivated to build fluency as new tools are introduced.
Demonstrated ability to produce clean, well-organized analytical work—data that is accurate, clearly structured, and ready for a manager or team to build on and act from.
Analytically precise: you hold a high personal bar for data accuracy, take ownership of the work you produce, and don’t let outputs move forward until you’re confident they’re right.
Commercially curious: you want to understand why the numbers matter, not just how to produce them—and you actively connect your analytical work to business outcomes like margin, revenue, and promotional performance.
Clear and organized communicator: you present data and analysis in a way that is easy to follow—well-labeled, logically structured, and free of ambiguity about what you’re showing and what it means.
AI-partnership mindset: you engage with pricing agents and agentic tools with genuine curiosity and appropriate rigor—applying outputs carefully, asking questions when something doesn’t look right, and grounding your work in ethical and brand-aligned judgment.
Eager to grow: you bring genuine interest in how pricing, AI, and retail intersect, actively seek to build your skills as the tools and function evolve, and approach your work with a test-and-learn mindset.

Responsibilities

Prepare and maintain pricing and promotional data for assigned brand work streams—pulling, cleaning, and organizing retail data sets so they are accurate, complete, and ready for analysis and modeling.
Run pricing models and scenario analyses under the direction of the Manager—applying elasticity inputs, sensitivity parameters, and promotional variables to generate outputs that are accurate, well-structured, and ready for review.
Apply and quality-check outputs from pricing agents across assigned categories—validating data inputs, flagging anomalies or inconsistencies, and ensuring outputs are accurate before they move forward in the analytical workflow.
Support in-season monitoring of pricing actions for assigned workstreams—tracking performance against plan, flagging variances, and surfacing data that helps the team identify risks or optimization opportunities quickly.
Use AI reporting tools and pricing platforms as a daily analytical tool—interrogating outputs with a critical eye, maintaining data integrity, and escalating to the Manager when outputs require additional human review before informing a decision.
Assemble analytical work into clean, well-organized supporting materials—building the data packages, tables, and summaries that your manager brings to business reviews and stakeholder discussions.
Prepare data pulls, performance summaries, and analytical inputs for weekly and monthly business reviews—ensuring pricing performance across assigned categories is accurately captured and clearly organized for the team to build on.
Develop your ability to translate analytical outputs into plain commercial framing—connecting what the data shows to what it means for margin, revenue, or promotional performance, and communicating that clearly in your deliverables.
Respond to analytical requests from the pricing team with accuracy and care, building a track record as someone who can be counted on to deliver clean, well-organized work on time.
Contribute to the ongoing training and refinement of the brand's pricing agents—documenting instances where outputs fall short, noting patterns in errors or gaps, and sharing observations with the team to improve model performance over time.
Help build shared documentation and analytical standards for the team—capturing what good looks like in data preparation, output validation, and model quality review so that practices are consistent and repeatable as the function grows.
Bring a curious, builder’s mindset to a function that is being created from scratch—asking questions, trying new approaches, and actively contributing ideas about how this team’s analytical processes can work better as it scales.