Staff Data Analyst – Returns

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and sustain dashboards and automated reporting for key performance indicators — return rate, days-to-refund, refund accuracy, inventory, and defect rates categorized by return center, carrier, and category; ensure data integrity and governance within the team.

• Evaluate and enhance warehouse productivity — analyze throughput per hour (TPH), units per shift, and team performance; perform workforce analytics to optimize staffing levels, scheduling, and skill allocation; forecast labor needs and pinpoint inefficiencies.

• Diagnose and enhance refund accuracy and quality — investigate issues with delayed or incorrect refunds and establish preventive monitoring; analyze refurbishment metrics (Grade-A rate, bin grades, rework defects); identify process gaps and root causes.

• Recognize and implement cost-saving measures — quantify opportunities for improvement in labor efficiency, materials, processing errors, shrinkage, and network optimization; prioritize initiatives based on impact and support return on investment (ROI) modeling for capital and staffing allocations.

• Develop predictive models and anomaly detection systems — alert on processing delays, declines in quality, and cost increases in real time; optimize the performance of reverse logistics networks and address refund pipeline bottlenecks.

• Collaborate on system enhancements and cross-functional projects — work with engineering and operations on data instrumentation; contribute to initiatives aimed at improving customer experience and optimizing the supply chain.

⛳️ Requirements

• A bachelor's degree in a quantitative field (e.g., Economics, Mathematics, Statistics, Engineering, Physics, Computer Science, Industrial Engineering); a master's degree is preferred.

• Over 7 years of relevant experience in data analytics, operations analytics, or supply chain analytics, ideally with a background in returns, reverse logistics, or warehouse operations.

• Advanced SQL expertise; capacity to write complex queries, enhance performance, and manage large-scale transactional datasets.

• Proficient in Python or R for statistical analysis, data modeling, and exploratory data analysis.

• Strong analytical abilities: adept at defining metrics, diagnosing underlying causes, and translating data insights into practical business recommendations.

• Experience with dashboarding and data visualization tools (such as Looker, Tableau, Sigma, or equivalent); knowledge of automation and alerting frameworks.

• High proficiency with AI tools to enhance productivity, reveal insights, and expedite analysis.

• Exceptional written and verbal communication skills; capable of conveying complex analyses to both technical and non-technical audiences.

• Demonstrated ability to manage multiple projects, prioritize tasks effectively, and deliver results in a fast-paced environment.

• Strong sense of ownership: self-motivated, proactive, and accountable for comprehensive quality and impact.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health benefits including medical, dental, and vision coverage.

• Generous retirement savings plan with employer matching.

• Opportunities for professional development and continuous learning.

• Flexible working hours and remote work options.