Korean Bilingual Data Analyst

Job Title: Logistics Risk Analyst

Clint: Samsung

Rate: $38-$40

Work Location: 3 MacArthur Place, Santa Ana, CA, USA

Work Schedule: Fully onsite

Length of Assignment: 12 months

• Bilingual Korean not required but strongly preferred

Education and Years of Experience:

• Bachelor’s degree in Data Analytics, Supply Chain, Engineering, Statistics, or related field.
• 2 years of experience in logistics analytics, operations analytics, or supply chain data analysis.

Top Skills:

• Excel(Pivot, Lookup, data matching & compare),
• Communication
• Analysis

Role Summary

Logistics Risk Analyst focuses on data-driven identification, analysis, and monitoring of logistics risks. This role serves as the analytical engine of the logistics risk management function, transforming operational data into actionable insights.

Key Responsibilities

• Analyze logistics data from TMS, WMS, ERP, and claims systems to identify risk patterns and anomalies.
• Develop and maintain logistics risk dashboards, KPIs, and early-warning indicators.
• Track trends in loss, damage, delay, and service failures.
• Support root cause analysis with quantitative evidence and data modeling.
• Prepare regular risk reports and ad-hoc analyses for management review.
• Partner with IT and operations teams to improve data quality and system integration.
• Support audits, compliance reviews, and risk assessments with data analysis.
• Recommend process improvements based on data findings.

Qualifications:

• Bachelor’s degree in Data Analytics, Supply Chain, Engineering, Statistics, or related field.
• 2 years of experience in logistics analytics, operations analytics, or supply chain data analysis.
• Hands-on experience with Excel, SQL, and BI tools (Power BI, Tableau, etc.).
• Familiarity with TMS/WMS and logistics performance metrics.
• Experience handling large datasets and building dashboards.

Core Competencies

• Strong analytical and quantitative skills
• High attention to detail and data accuracy
• Ability to translate data into business insights
• Structured analysis