Manager - Pricing Strategy & Analytics

About the Role

The scope spans three areas:

Strategic pricing principles. Drive the definition of the brand's strategic pricing principles and pricing architecture as part of the refresh of its pricing strategy, including how success is defined and measured, and drive adoption across cross-functional teams.

Strategic discount budget. Own the strategic positioning of discount spend across the mechanisms used to price products and communicate pricing to customers.

In-season analytics. Reconcile in-season execution against forecasted performance and actuals, and make recommendations to Merchandise Planning and Company Planning (Finance) through ""what if"" scenarios and financial modeling of pricing strategies.

Reporting to the Brand Pricing Performance Lead, you will own outcomes across these areas, working within a single brand. You will manage relationships with cross-functional partners across Merchandising, Planning, Company Planning, Commerce & Experience, and Pricing Operations, and turn complex internal and external data into clear, decision-ready insight that drives strategic alignment on what the brand should do.

What You'll Do

Own Pricing Principles, Discount Budget, and Pricing Architecture

• Develop and run repeatable analytics that inform pricing strategy, pricing architecture, and pricing tactics, applying rigorous methods to produce recommendations grounded in accurate data.
• Develop and own the pricing guardrails adopted by the cross-functional team, including measuring their effectiveness and driving adoption.
• Own the strategic discount budget for the brand, and the in-season reconciliation of actions taken against it.
• Define how success is measured for the brand's pricing principles, and report on it.

Deliver In-Season Analytics and Reporting

• Reconcile in-season pricing execution with forecasted performance and actuals, and flag where the brand is off plan.
• Build "what if" scenarios and financial models of pricing strategies, and package recommendations for Merchandise Planning and Company Planning (Finance).
• Develop and manage aggregated data analysis and reporting that turns findings into actionable, visual reports and research-driven recommendations.

Support Competitive Price Positioning

• Analyze internal and external data to set and maintain competitive price positioning, building the models and benchmarks the team relies on.
• Track and report on competitive price positioning, validating that the brand is executing against aligned benchmarks and flagging where it is not.

Partner Cross-Functionally

• Own relationships with internal stakeholders and external partners on strategic pricing and analytics projects.
• Work autonomously with peers and share clear findings with the leadership team across Merchandising, Planning, Company Planning, Commerce & Experience, and Pricing Operations.
• Translate analytics into the "what" and the "so what" for business owners and finance partners.
• Identify opportunities for continuous process improvement and support cross-functional decision-making.

Apply AI and Build the Function

• Apply and validate outputs from pricing agents, confirming data integrity and business logic before recommendations are finalized, and contribute to training and refining those agents.
• Simplify and automate repeatable processes, contributing to the tools and workflows the function will run on as it scales.
• Review and provide feedback on analyses from the analyst on the team, and collaborate with them on ad-hoc pricing projects.

Who You Are

Experience & Qualifications

• Bachelor’s degree required. Preferred emphasis on analytics, mathematics, business, supply chain, industrial engineering, finance, accounting, or economics.
• 6+ years of experience in pricing analytics, competitive intelligence, or a related field, with direct exposure to retail or consumer products pricing.
• Clear communication skills and the ability to tailor messaging to various levels of the organization
• Able to manipulate very large data sets to interpret patterns and learnings; strong understanding of data structures and algorithms.
• Proficiency in Microsoft Excel with an aptitude to learn technical applications quickly; proficiency in Python and/or SQL preferred.
• Financial and business acumen: ability to evaluate financial and business indicators and translate data into actionable information to drive results; proficiency in retail math preferred.
• Experience or an aptitude for AI-enabled analytics tools; comfortable validating outputs from pricing agents and applying judgment to AI-generated recommendations.

Leadership & Mindset

• Analytically exacting: you hold a high personal bar for accuracy, take ownership of your models and assumptions, and don’t let outputs go forward until you’re confident they’re right.
• Commercially curious: you connect your analytical work to business outcomes (margin, revenue, promotional ROI, customer impact), and you develop recommendations that reflect that understanding, not just technical outputs.
• Clear and direct communicator: you can distill analytical complexity into plain, well-structured commercial framing that non-analytical partners can read and act on.
• AI-partnership mindset: you engage with agentic tools and pricing agents as a critical collaborator, fluent enough to use them effectively, rigorous enough to catch when they’re wrong, and grounded in ethical and brand-aligned judgment.