Manager, In-Season Pricing Enablement

$112,100 - $148,500/Yr

Old Navy - San Francisco, CA

Full-time - Mid Level

San Francisco, CA

10,001+ employees

Clothing, Clothing Accessories, Shoe, and Jewelry Retailers

About the position

The Manager of In-Season Pricing Enablement at Old Navy is responsible for planning and operating the in-season pricing process within the Merchandise Planning function. This role involves facilitating key meetings, creating reports, and influencing leadership decisions to achieve brand-level gross margin targets. The position requires strong communication skills, data-driven decision-making, and the ability to manage cross-functional teams effectively.

Responsibilities

• Own the meeting agenda for the Promo Review and Midweek Business Review meetings.
• Create reporting for the Promo Review and Midweek Business Review that supports in-season meetings.
• Facilitate the Promo Review and Midweek Business Review meetings to achieve objectives.
• Influence senior leaders on the Merchandise Planning team to make decisions that meet gross margin targets.
• Negotiate next steps and align with cross-functional team leaders on necessary actions.
• Recap meetings to attendees and share decisions and next steps with the MPLT.
• Manage the intake process for in-season analytics requests and prioritize them with the Pricing Operations team.
• Utilize forecasts and results reporting to drive meeting outcomes.
• Attend MF meetings to understand business context and evolving risk scenarios.

Requirements

• 5+ years of experience in merchandise planning roles with an undergraduate degree or 3 years with a graduate degree.
• Experience in apparel retail or CPG environments is mandatory.
• Strong communication skills for data-driven recommendations and storytelling.
• Ability to follow through on commitments and demonstrate a bias for action.
• Motivated to learn new concepts and apply them to achieve business outcomes.
• Strong understanding of retail math and yield management principles.
• Ability to manipulate data sets to interpret patterns and learnings.

Nice-to-haves

• Preferred emphasis on supply chain, business, mathematics, industrial engineering, computer science, or economics.

Benefits

• 401(k) matching
• Dental insurance
• Employee stock purchase plan
• Health insurance
• Life insurance
• Paid time off
• Store discount