Staff Data Analyst

At Guitar Center, Analytics helps teams make better decisions that drive customer and business value. We are looking for a Staff Data Analyst to serve as the senior analytics partner to Merchandising and adjacent commercial teams.

This senior individual contributor will identify and size opportunities, frame ambiguous questions, design credible measurement, and influence leaders to act. The ideal candidate combines retail or commercial judgment, financial acumen, advanced analytical skills, and a track record of how organizations use data.

PLEASE NOTE: while the strong preference is to hire someone within a commutable distance from Westlake Village, CA, who can work onsite Tuesday, Wednesday and Thursday every week, we are open to hiring remotely from the following states: California, Indiana, Missouri, and Utah.

Key Responsibilities

• Merchandising partnership: Partner with Merchandising leaders to guide decisions across pricing, assortment, allocation, promotions, inventory, vendors, and visual merchandising.

• Opportunity prioritization: Identify, size, and sequence high-value revenue, margin, inventory, and customer opportunities with Merchandising leaders and analytics management.

• Analytical leadership: Translate ambiguous commercial questions into analytical and measurement plans; conduct rigorous analysis and develop proof-of-concept analyses when useful.

• Solution direction: Define needed data and capabilities, then partner with Data Engineering, BI, and other Sr. Analysts to operationalize durable solutions.

• Experimentation and causal measurement: Guide hypothesis design, comparison groups, and interpretation, accounting for seasonality, selection bias, halo, and cannibalization effects.

• Influence and enablement: Turn complex findings into clear recommendations and build Merchandising fluency in using data and BI to diagnose performance, test ideas, and act confidently.

• Methods and team partnership: Partner with analytics management to define and document Guitar Center's policies and standards for experimentation and causal inference.