Pricing Analytics Manager: AI-Driven Strategy & Insights

Gap; New York (NY); On-site; USD 119,000 - 155,000; Full time

Benefits offered by this job

Merchandise discount (50% at Gap)

Competitive PTO plan

401(k) with company match

Employee stock purchase plan

Comprehensive health benefits

Job summary

Gap Inc. is seeking a Manager - Pricing Analytics in New York to own pricing principles, discount strategy, and in-season analytics. You will collaborate with Merchandising, Planning, Finance, and Pricing Ops to drive data-driven pricing decisions that affect margin and revenue.

The role requires 6+ years in pricing analytics, strong data interpretation skills, and proficiency with Excel, Python, and SQL. You will lead analytics initiatives and mentor team members in a fast-paced retail setting.

Qualifications

• Bachelor's degree required; analytics, finance, or related field preferred.
• 6+ years in pricing analytics, competitive intelligence, or related field.
• Ability to manipulate very large data sets and translate into insights.
• Proficiency in Excel; Python/SQL preferred for analysis.
• Financial and business acumen with market awareness.

Responsibilities

• Develop repeatable analytics to inform pricing strategy and tactics.
• Own pricing principles, discount budget, and pricing architecture.
• Deliver in-season analytics and reporting with scenario modeling.
• Support competitive price positioning and cross-functional collaboration.
• Apply AI outputs, validate data integrity, and simplify processes.

Skills

Pricing analytics

Data interpretation

Communication

AI-enabled analytics tools

Strategic thinking

Education

Bachelor's degree

Tools

Python

SQL

Excel

Job description

Gap Inc. is seeking a Manager - Pricing Analytics in New York to own pricing principles, discount strategy, and in-season analytics. You will collaborate with Merchandising, Planning, Finance, and Pricing Ops to drive data-driven pricing decisions that affect margin and revenue.

The role requires 6+ years in pricing analytics, strong data interpretation skills, and proficiency with Excel, Python, and SQL. You will lead analytics initiatives and mentor team members in a fast-paced retail setting.