Senior Pricing & Merch Analytics Lead

McKinsey & Company; Boston (MA); On-site; USD 99,000 - 121,000; Full time

Benefits offered by this job

Competitive salary

Global opportunities

World-class benefits

Job summary

McKinsey & Company, in our Growth, Marketing & Sales practice, is seeking analytical professionals to join one of our North American offices. You will work in teams to tackle strategic, organizational, and operational challenges for clients and help deliver pricing, merchandising, and promotion capabilities using Periscope and cloud-based analytics.

This role emphasizes ownership, cross-functional collaboration with data scientists, engineers, and product experts, and the ability to translate

Qualifications

• Bachelor's degree in business or engineering required.
• 2+ years in consulting, analytic pricing, merchandising or technology delivery.
• Experience with data science, visualization, statistics in CPG/retail preferred.
• Ability to collaborate with product owners, PMs, and data teams.
• Experience in matrixed environments requiring stakeholder influence.
• Ability to articulate solutions to diverse stakeholders.

Responsibilities

• Collaborate in teams to tackle strategic, organizational, and operational challenges.
• Help deliver capabilities for merchandising and pricing strategies.
• Engage with client sponsors to drive adoption of Periscope solutions.
• Contribute to end-to-end solution deployments and upgrades.

Skills

Analytical thinking

Data science basics

Stakeholder communication

Team collaboration

Education

Bachelor's degree in business or engineering

MBA

Tools

Cloud platforms

Data visualization tools

Job description

McKinsey & Company, in our Growth, Marketing & Sales practice, is seeking analytical professionals to join one of our North American offices. You will work in teams to tackle strategic, organizational, and operational challenges for clients and help deliver pricing, merchandising, and promotion capabilities using Periscope and cloud-based analytics.

This role emphasizes ownership, cross-functional collaboration with data scientists, engineers, and product experts, and the ability to translate