Data Analyst 1 (Korean Bilingual)

Job Title: Logistics Data Analyst 1 (#17098-1)

Position Details

• Role: Data Analyst 1
• Pay Rate: Up to $42.00 / hr (W2)
• Location: 3 MacArthur Place, Santa Ana, CA (Fully Onsite)
• Duration: 12 Months (04/20/2026 – 04/19/2027)
• Language: Bilingual Korean (Strongly Preferred, not required)

Role Summary The Logistics Risk Analyst serves as the analytical engine for the logistics risk management team. This role focuses on data-driven identification, analysis, and monitoring of risks, transforming complex operational data from TMS, WMS, and ERP systems into actionable business insights.

Top Skills

• Advanced Excel: Mastery of Pivot Tables, VLOOKUP/XLOOKUP, and complex data matching/comparison.
• Data Analysis: Experience handling large datasets and performing root cause analysis.
• Communication: Ability to translate quantitative evidence into clear reports for management.

Key Responsibilities

• Risk Pattern Identification: Analyze data from TMS, WMS, ERP, and claims systems to detect anomalies and risk patterns in the supply chain.
• Monitoring & Dashboards: Develop and maintain logistics risk dashboards, KPIs, and early-warning indicators for loss, damage, and service failures.
• Reporting: Prepare regular and ad-hoc quantitative analyses to support management review and audit processes.
• Process Improvement: Partner with IT and operations to improve data quality and recommend process enhancements based on data findings.
• Root Cause Analysis: Support operational teams with quantitative evidence and data modeling to prevent disruptions.

Qualifications

• Education: Bachelor’s degree in Data Analytics, Supply Chain, Engineering, Statistics, or a related field.
• Experience: 2+ years of professional experience in logistics, operations, or supply chain data analysis.
• Technical Tools: Hands-on experience with Excel, SQL, and BI tools (Power BI, Tableau, etc.).
• Industry Knowledge: Familiarity with TMS/WMS systems and standard logistics performance metrics.

Core Competencies

• High attention to detail and data accuracy.
• Ability to translate complex data into structured, easy-to-understand business insights.
• Strong problem-solving skills within a fast-paced environment.