Pricing and Data Manager

Description

The Pricing and Data Manager leads the analytics team to drive data-informed decisions across merchandising, marketing, e-commerce, operations, and customer experience. They are responsible for developing and executing pricing strategies that enhance profitability, optimize performance, and ensure market competitiveness across all retail channels. This role combines data analysis with cross-functional collaboration to improve business outcomes and support strategic growth.

• Lead and mentor the analytics team to deliver high-quality reports, dashboards, and insights.
• Collaborate with cross-functional teams to align analytics with business needs.
• Develop and maintain dashboards and KPIs for key retail metrics (sales, traffic, pricing, etc.).
• Analyze customer behavior to support personalization, segmentation, and retention strategies.
• Apply forecasting, A/B testing, and predictive modeling to guide decisions.
• Ensure data accuracy and integrity in partnership with IT and data engineering.
• Communicate insights and recommendations clearly to senior leadership.
• Foster a data-driven culture and build organizational analytics capabilities.
• Create and manage pricing strategies to drive revenue, margin, and category performance.
• Monitor sales, pricing, competition, and customer trends to identify risks and opportunities.
• Lead pricing reviews with key stakeholders to align on strategy and performance.
• Oversee pricing throughout the product lifecycle, including promotions and markdowns.
• Manage pricing tools and reporting for accuracy and timeliness.
• Support implementation of pricing systems and automation in partnership with IT and business teams.
• Maintain pricing consistency and governance across all channels and locations.

• Bachelor’s degree in Data Science, Statistics, Mathematics, Business, Computer Science, or related field preferred.
• 5+ years of experience in data analytics, with at least 2 years in a managerial or lead role preferred.
• Experience in retail, e-commerce, or consumer-facing industries.
• Advanced proficiency in SQL and data visualization tools (e.g., Power BI, Tableau, Looker).
• Strong analytical mindset with a deep understanding of statistical analysis, forecasting, and data modeling.
• Proven ability to communicate complex data in a simple, compelling way to non-technical audiences.
• Ability to manage multiple projects in a fast-paced environment.