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Data Support Intern

Rhenus logistics
Rhenus logistics (Bangkok City, Thailand)
Bangkok, Thailand 🇹🇭
Rhenus logistics
The Rhenus Group is one of the leading logistics specialists with global business operations and annual turnover amounting to EUR 7.5 billion. 40,000 employees work at 1,320 business sites in more than 70 countries and develop innovative solutions along the complete supply chain. Whether providing transport, warehousing, customs clearance or value-added services, the family-owned business pools its operations in various business units where the needs of customers are the major focus at all times.

About this position

We are seeking a detail-oriented individual to assist our Sustainability Team with critical data verification and analysis projects over a 3-month period from January to March 2025. This role provides the chance to contribute to meaningful sustainability initiatives, engage with global standards, and develop valuable skills in data analysis, assurance processes, and ISO verification.

Responsibilities

You will be contributing to that vision by…
• Coordinate Data and Evidence Verification: Review the greenhouse gas inventory and supporting documents to ensure accuracy and completeness for ISO 14064 verification.
• Support GHG Data Compilation and Analysis: Assist the Sustainability Team in organizing and analyzing GHG data to facilitate the external verification process.
• Prepare Documentation for the Assurance Process: Help prepare, organize, and maintain documents required for ISO 14064 assurance.
• Assist with Audit-Related Administrative Tasks: Perform administrative tasks to maintain a well-organized, audit-ready environment.

Requirements

What skills & experience you’ll bring to us
• Open to final-year university students seeking an internship or recent graduates looking for a temporary role.
• Proficiency in Excel with basic data management skills.
• Excellent verbal and written communication skills in English.
• Strong organizational skills with the ability to meet deadlines.
• High attention to detail and comfort working with large, diverse datasets.