Joint Head of Pricing, Promotions & Analytics at BP in Louisville, KY

  • Company: BP
  • Location: United States of America - Kentucky - Louisville
  • Job type: full time
  • Workplace: onsite
  • Posted: 2026-10-30

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Job description

Job Family Group: Marketing Group Job Description: The Head of Pricing & Data Analytics – Merchandising is responsible for building and leading the pricing and analytics capabilities that support the Merchandising organization across BP and TA brands . This role will use data, analytics, competitive intelligence, customer insights, and advanced pricing technology to improve sales, margin, inventory productivity, and the overall customer value proposition. The position will play a key leadership role in helping develop, implement, and expand the use of BP's enterprise pricing tool/system across its brands . This includes partnering with Merchandising, Pricing, Operations, Loyalty, and other key stakeholders to determine how the platform can best support the business and ensuring its capabilities translate into practical, actionable pricing recommendations. This leader will manage a team of data scientists and analytics professionals responsible for turning complex data into clear, actionable recommendations. The team will provide insights and recommendations across all merchandise categories, including base pricing, promotional pricing, markdowns, competitive positioning, assortment, inventory, and other sales and margin opportunities . The role will also own and manage the Store Archetype Strategy , ensuring merchandising decisions reflect the different customers, missions, sales opportunities, and operating environments across the store network. Additionally, this leader will ensure that pricing, promotional, customer, and store archetype insights effectively support EarnifyPro and other loyalty programs as part of the overall Merchandising strategy. The role will partner with Loyalty and other key stakeholders to help develop more relevant offers, increase customer engagement, and ensure loyalty strategies complement the broader pricing and promotional strategy. The overarching objective is to use data, analytics, pricing technology, and customer insights to help put the right products, in the right stores, at the right price, in the right quantities, with the right offers for the right customers. Key Responsibilities Enterprise Pricing Strategy & Pricing System Help develop, implement, and continuously improve the use of the enterprise pricing tool/system across BP and TA brands . Work across the broader BP organization to identify opportunities to leverage the pricing platform's advanced analytics and AI capabilities. Partner with Category Management and Merchandising leadership to establish an effective and consistent pricing framework while recognizing differences in customers, markets, brands, and store formats. Help translate the capabilities of the pricing system into practical business processes and actionable recommendations for Category Managers and leadership. Drive adoption and effective utilization of the pricing system within Merchandising. Develop and provide data-driven recommendations for: Base and everyday pricing Promotional pricing Markdown and clearance strategies Competitive price positioning Price zones and geographic pricing Price elasticity and customer response Margin and sales optimization Establish processes for regularly reviewing pricing performance and identifying opportunities for improvement. Ensure pricing recommendations balance customer value, competitive position, sales growth, margin, and long-term category health . Develop clear reporting that allows leadership and Category Managers to understand the expected and actual impact of pricing decisions. Measure results and continuously refine pricing strategies based on performance. Data Science & Advanced Analytics Lead, develop, and mentor a team of data scientists and analytics professionals supporting Merchandising. Establish priorities for the team based on the most significant sales, margin, inventory, pricing, and customer opportunities. Translate large and complex data sets into practical recommendations that Category Managers and bu

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