Analyst - Pricing Optimization

Gap Inc.•San Francisco, CA

About The Position

The Pricing Optimization Associate supports pricing analytics and decision support across the Gap brand. The role completes foundational analyses and prepares inputs for pricing strategy, price testing, competitive pricing insights, pricing architecture, promotion scenario planning, markdown optimization, yield management, and forecast tuning. As part of Gap Inc.'s Pricing, Planning Analytics, and Inventory Optimization function, the role works with business partners and experienced team members, following consistent decision standards, approved AI-enabled tools, and transparent analytical methods. The position supports recurring analyses, scenarios, reporting, and recommendations; checks data and outputs for accuracy; and prepares clear summaries and decision-support materials. It also coordinates with cross-functional partners to gather inputs and support approved price actions, while building knowledge of Gap Inc.'s planning, pricing, inventory, merchandising, and financial processes. The role is expected to deliver accurate, timely work, communicate progress and risks, seek feedback, and contribute practical ideas to improve recurring work and insight usability.

Requirements

Bachelor's degree in business, economics, finance, analytics, mathematics, statistics, engineering, retail, or a related field.
At least 1 year of relevant analytical experience in retail, planning, pricing, inventory, finance, data analytics, consulting, or a related field.
Foundational analytical, modeling, communication, and storytelling skills, with the ability to turn data into clear findings and practical next steps.
Comfort using Excel and data tools.
Ability to follow established methods, ask thoughtful questions, and communicate clearly.
Commercial curiosity and attention to detail, with interest in how customer, product, revenue, margin, inventory, service, and execution factors connect.
Ability to apply common standards while learning relevant brand context.
Comfort using AI-enabled tools and agentic workflows with human review, appropriate validation, and timely escalation of exceptions or risks.
Collaborative approach, ability to build trust and respond with urgency, openness to feedback, and contribution to continuous improvement.

Nice To Haves

Exposure to retail, apparel, consumer products, consulting, finance, data analytics, planning, pricing, inventory, or merchandising.
Exposure to BI platforms, SQL, Python, forecasting, optimization, pricing tools, or AI-enabled workflows.

Responsibilities

Complete recurring pricing analyses, data preparation, model inputs, scenario runs, reporting, and recommendation materials using established methods and templates.
Check data and outputs for completeness and accuracy; identify inconsistencies, risks, and patterns, and escalate questions when needed.
Prepare clear summaries, visuals, and decision-support materials explaining findings and relevant business implications.
Maintain accurate records of assumptions, outputs, approvals, actions, and hindsight in the decision log.
Support pricing, promotion, markdown, and yield-management scenarios, learning how revenue, margin, sell-through, customer value, and inventory exposure shape trade-offs.
Analyze elasticity, competitive, category, channel, and customer signals and summarize implications for pricing recommendations and guardrails.
Coordinate with GMM, Merchandising, Planning, Inventory Optimization, Pricing Operations, and Finance to gather inputs, confirm execution constraints, and support approved price actions.
Share analyses with peers across Planning, Pricing, and Inventory Optimization to connect work and reduce siloed execution.
Use approved AI-enabled tools, models, dashboards, and agents responsibly; validate outputs against source data, business context, and known constraints, and seek guidance for exceptions.
Build knowledge of Gap Inc. planning, pricing, inventory, merchandising, and financial processes and apply it to assigned work.
Follow established workflows and contribute practical ideas to improve templates, data quality, recurring work, and the usability of insights.
Deliver accurate, timely work; communicate progress and risks; seek feedback; and bring curiosity, responsiveness, and a service mindset to business partners and team members.