Supply Chain Intern (Jan - Jun 2027)

Cartier; Singapore; On-site; SGD 17,000 - 22,000; Full time

Job summary

Cartier is seeking a Supply Chain Intern in Singapore to gain hands-on experience in a dynamic environment. You will support operations through data analysis, project management, and operational support, and collaborate with cross-functional teams to drive improvements.

You will work with SAP, Excel, Power BI, Looker, and Python to develop dashboards, analyze data, and assist with inventory control and process optimizations.

Qualifications

• Pursuing a Bachelor’s or Master’s in Supply Chain, Engineering or related field.
• Basic programming knowledge (Python, SQL) required.
• Strong analytical skills to handle large datasets.
• Proficiency in Excel; data visualization helpful.
• Familiarity with SAP or ERP systems is a plus.
• Fluent in English; Asian language is a plus for collaboration with SEAO team.

Responsibilities

• Extract, cleanse, and analyze large datasets from SAP, Excel, and internal databases.
• Develop dashboards and reports using Power BI and Looker to visualize KPIs.
• Utilize Python for data manipulation and automation of reporting processes.
• Present data insights to the supply chain team for data-driven decision-making.
• Collaborate with SEAO teams to identify efficiency improvements and process enhancements.
• Assist with inventory control, including quality checks and discrepancy resolution.

Skills

Python

SQL

Excel

Data analysis

Communication

Attention to detail

SAP familiarity

Education

Bachelor’s or Master’s in Supply Chain or Engineering

Tools

Power BI

Looker

SAP

Job description

How You Will Make An Impact

Join our team and gain hands-on experience in a dynamic supply chain environment! As a Supply Chain Intern, you will play a vital role in supporting our operations through data analysis, project management, and operational support. This internship offers the opportunity to have a glimpse into our Supply Chain function and develop your analytical skills, contribute to process improvements, and collaborate with cross-functional teams.

Your Key Responsibilities Include

Data Analysis & Reporting:

• Extract, cleanse, and analyze large datasets from various sources (e.g., SAP, Excel, internal databases).
• Develop and maintain interactive dashboards and reports using MS Power BI and Looker to visualize key performance indicators (KPIs) and identify trends.
• Utilize Python for data manipulation, statistical analysis, and automation of reporting processes.
• Present data insights and recommendations to the supply chain team to support data-driven decision-making.
• Contribute to the development and improvement of data models to ensure data accuracy and consistency.

Operational Support

• Support the preparation of business presentations for management reviews and strategic planning sessions.
• Assist with project management activities, including tracking project timelines, coordinating meetings, and documenting action items.
• Participate in technical testing of SAP ERP system updates and enhancements.
• Collaborate with SEAO teams to identify and resolve operational inefficiencies and improve supply chain processes.
• Assist with inventory control activities, including quality checks, reconciliations, and discrepancy resolution.
• Provide administrative and ad-hoc support to SEAO Operations Department as needed.

Your Profile/Key Skills

• Pursuing a Bachelor’s or Master’s degree in Supply Chain, Engineering, or a related field
• Familiarity with basic programming languages (Python, SQL) is essential
• Strong analytical skill to analyze large data sets and present findings in concise manner
• Strong proficiency in Excel is a must; data visualization tool is a plus
• Good organizational, communication, and problem-solving skills
• Self-starter with a high integrity, and strong attention to detail
• Familiarity with SAP or other ERP systems is an added advantage
• Fluent in English; an additional Asian language is a plus for effective collaboration with the SEAO team