Data Analyst

Job description

Company Description Avery Dennison (NYSE:AVY ) is a global materials science and digital identification solutions company that provides a wide range of branding and information solutions that optimize labor and supply chain efficiency, reduce waste, advance sustainability, circularity and transparency, and better connect brands and consumers. Our products and solutions include labeling and functional materials, radio frequency identification (RFID) inlays and tags, software applications that connect thy physical and digital, and a variety of products and solutions that enhance branded packaging and carry or display information that improves the customer experience. Serving an array of industries worldwide - including home and personal care, apparel, general retail, e-commerce, logistics food and grocery, pharmaceuticals and automotive - we employ approximately 35,000 employees in more than 50 countries. Our reported sales in 2025 were $8.9 billion. Learn more at www.averydennison.com . AVERY DENNISON IS PROUD TO BE CERTIFIED GREAT PLACE TO WORK IN AUSTRALIA , CHINA , INDIA , JAPAN , SINGAPORE , MALAYSIA , THAILAND AND VIETNAM , AND RECOGNIZE AS ONE OF THE BEST COMPANIES TO WORK FOR IN ASIA IN GREATER CHINA AND VIETNAM . Job Description ABOUT YOUR ROLE As a Data Analyst, you will play a vital role in the manufacturing or supply chain environment, acting as the bridge between data analytics and system development. Working directly across multiple cloud platforms (including GCP, OCI, and other data storage platforms), you will collaborate with stakeholders not only to analyze data for strategic insights but also to build, automate, and deploy end-to-end digital solutions that optimize daily operational efficiency. YOUR RESPONSIBILITIES WILL INCLUDE Digital Solutions & Automation: Develop and deploy end-to-end digital solutions, including web applications (FastAPI/Flask/React) and automated workflows (Apps Script/Python/cloud integrations) to optimize operational efficiency and reporting processes. Data Analytics: Extract, process, and analyze data using Google Apps Script, SQL, and Python from various platforms such as Google Workspace, Microsoft Office, local MES, IoT systems, and other data storage solutions to create interactive dashboards and communicate actionable findings. AI & Cloud Solutions Adoption: Participate in projects utilizing AI-driven tools. Build integrated AI applications involving Generative AI APIs and agentic AI tools to support data analysis in cloud platforms like Google Cloud Platform (GCP) and Oracle Cloud Infrastructure (OCI). Documentation, Quality & Continuous Improvement: Document system architectures, develop and maintain data validation routines, and drive continuous improvement of data processes and tool utilization across the Google ecosystem and other platforms. Team Enablement & Training: Facilitate hands-on training sessions for cross-functional team members to improve their proficiency in interpreting data and using self-service tools for daily operational decision-making. Qualifications Requirements: Less than 2 years of experience (including internships or part-time roles). Target majors: Management Information Systems (highly preferred), Information Systems, Information Technology. Core Competencies: Solid knowledge of database design, data normalization, and data querying with SQL. Understanding of basic data analysis and processing workflows. Relevant coursework or experience: programming techniques, data structures and algorithms, API integration into systems, using GitHub for code management. Proficiency in Python for Software Engineering (OOP, Git, experience with API/Web frameworks is a big plus). Project experience: Have a graduation or internship project related to building data pipelines, web applications, or practical data management systems. Proficient in Google Workspace products (Sheets, Apps Script, etc.). Analytical mindset with strong logical thinking. Eagerness to learn and adapt to new technologies, especially within cloud environments. Ability to communicate data insights clearly to non-technical audiences. Team-oriented, proactive, and self-motivated. Preferred Qualifications: Hands-on experience working with Generative AI or agentic AI tools. Background or coursework in manufacturing, industrial engineering, or supply chain data management systems. Hands-on experience working with Google APIs or integrating automation within Google Workspace is a strong advantage. Awareness of data security and privacy best practices. Experience with Google Cloud Platform (GCP), Oracle Cloud Infrastructure (OCI), or similar platforms is a plus. Additional Information