Staff Data Analyst – Returns

🔥 12 hours ago

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Quince

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2018

💼 Consulting

📦 Logistics

🏭 Manufacturing

Consulting • Logistics • Manufacturing

Quince is a direct-to-consumer e-commerce retailer offering affordable luxury essentials across apparel, home goods, bedding, beauty, and accessories. The company emphasizes high-quality materials (cashmere, European linen, leather, silk), a factory-direct model to keep prices low, sustainable practices, and long return policies. Quince sells men's and women's clothing, baby and kids items, furniture and home decor, and lifestyle products through an online storefront with focus on honest pricing and value.

📋 Description

• Build and maintain dashboards and automated reporting for core KPIs — return rate, days-to-refund, refund accuracy, inventory, and defect rates by return center, carrier, and category; ensure data quality and governance across the team • Measure and optimize warehouse productivity — analyze TPH, units/shift, and team performance; conduct workforce analytics to optimize staffing levels, scheduling, and skill allocation; forecast labor demand and identify inefficiencies • Diagnose and improve refund accuracy and quality — investigate delayed/incorrect refunds and build preventive monitoring; analyze refurbish metrics (Grade-A rate, bin grades, rework defects); identify process gaps and root causes • Identify and drive cost reductions — quantify opportunities across labor efficiency, materials, processing errors, shrinkage, and network optimization; prioritize by impact and support ROI modeling for capital and staffing investments • Build predictive models and anomaly detection — flag processing delays, quality drops, and cost spikes in real time; optimize reverse logistics network performance and refund pipeline bottlenecks • Partner on system improvements and cross-functional initiatives — collaborate with engineering and operations on data instrumentation; contribute to customer experience and supply chain optimization efforts

🎯 Requirements

• Bachelor's degree in a quantitative discipline (e.g., Economics, Mathematics, Statistics, Engineering, Physics, Computer Science, Industrial Engineering), Master’s preferred • 7+ years of relevant experience in data analytics, operations analytics, or supply chain analytics—preferably with exposure to returns, reverse logistics, or warehouse operations • Expert-level SQL proficiency; ability to write complex queries, optimize performance, and work with large-scale transactional datasets • Proficiency in Python or R for statistical analysis, data modeling, and exploratory analysis • Strong analytical skills: ability to define metrics, diagnose root causes, and translate data insights into actionable business recommendations • Experience with dashboarding and data visualization tools (Looker, Tableau, Sigma, or similar); familiarity with automation and alerting frameworks • Strong proficiency with AI tools to increase productivity, surface insights, and accelerate analysis • Excellent written and oral communication; ability to explain complex analyses to both technical and non-technical audiences • Proven ability to manage multiple workstreams, prioritize effectively, and deliver in a fast-paced environment • Strong ownership mentality: self-directed, proactive, and accountable for end-to-end quality and impact.