Warehouse Quality Control Specialist - Quality Control

Warehouse Quality Control (QC) Specialist

Location: Chicago, IL area / Atlanta, GA area

Company Overview

YQN is a leading one-stop international logistics online services platform, offering comprehensive international logistics services, including FCL, LCL, air freight, rail service, trucking, customs clearance, warehousing, cargo insurance, bulk cargo service, port of destination services, etc.

We are designed to apply the internet and digital technology to visualize and optimize cross-border supply chain logistics to achieve the same efficiency and convenience as express delivery. ‘Simple shipping and easy freight’ is the mission of YQNLINK. We have developed strategic cooperative partnerships with leading ocean carriers and logistics service providers such as COSCO Shipping, Maersk Line, Sinotrans, etc.

We have built up the ocean and air transport network from China to the world and introduced a series of innovative product offerings such as the First-class FCL, First-class LCL, First-class Air Freight, realizing online quotation, online order, online logistics tracking and other abundant functions, to build a more efficient and intelligent cross-border supply chain logistics.

Position Overview：

This role is responsible for identifying, flagging, and tracking to closure the operational quality and risk issues across the warehouses in the assigned region. The position is highly data-driven: its core work is to surface risk through the production and analysis of data. It does not carry warehouse operations execution responsibilities and does not directly manage warehouse floor staff.

Key Responsibilities

1. Data Production: Planning, Validation, and Analysis

• Proactively expand and build the data sources required for quality management, converting on-site conditions that were previously unobservable into data that can be collected on an ongoing basis.
• Own the accuracy of data and the consistency of data definitions.
• Conduct data-based analysis, diagnosis, and root-cause identification of quality and risk issues.
• Build and maintain quality monitoring dashboards and analytical models.

2. Quality and Risk Early Warning

• Own early-warning responsibility for operational quality and risk across the warehouses in scope.
• Establish and maintain a tiered early-warning and escalation mechanism.
• Track reported issues through to closure, using data to verify whether problems have actually been resolved.

3. On-Site Inspection

• Conduct on-site inspections against established standards and deliver inspection reports with supporting evidence and prioritized corrective actions.
• Focus on identifying discrepancies between actual on-site conditions and system data, and convert such discrepancies into metrics that can be monitored on an ongoing basis.

4. Quality Improvement

• Deliver quality improvement recommendations and drive their implementation. Execution is owned by the operations team; this role is responsible for verifying outcomes.

Qualifications

• 3+ years of experience in warehouse operations, quality management, or a related field.
• Strong data analysis skills, with the ability to independently extract data, perform analysis, and deliver conclusions.
• Uses AI tools as a standard part of daily work, applying AI to data processing, analysis, report generation, and process automation.
• Able to convert repetitive monitoring and analysis work into automated or AI-driven processes, and codify them into reusable rules and methods rather than relying on repeated manual effort.
• Open to new AI tools and ways of working, with the ability to learn quickly and apply them to real business scenarios.
• Strong communication skills, with the ability to clearly present issues to warehouse supervisors and regional management and drive corrective action.
• Professional proficiency in Chinese speaking and reading is preferred

Preferred Qualifications

• Proficiency in Mandarin Chinese (listening, speaking, reading, and writing).
• Software development skills.
• Hands-on experience building AI agents, knowledge bases, or process automation.
• Background in Lean, Six Sigma, or 5S.