A full stack Data Scientist

Company Description

About Avery Dennison
Avery Dennison Corporation (NYSE: AVY) is a global materials science and digital identification solutions company. We are Making Possible™ products and solutions that help advance the industries we serve, providing branding and information solutions that optimize labor and supply chain efficiency, reduce waste, advance sustainability, circularity and transparency, and better connect brands and consumers. We design and develop labeling and functional materials, radio-frequency identification (RFID) inlays and tags, software applications that connect the physical and digital, and offerings that enhance branded packaging and carry or display information that improves the customer experience. Serving 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 2024 were $8.8 billion. Learn more at www.averydennison.com.

Job Description

The Full Stack Data Scientist will join the European Materials Group Finance team and tackle complex business problems to drive insights, improve efficiency, and unlock value. You will interact with business leaders, engage in data-driven discussions, and implement solutions from end-to-end. 

Ideally, you will be based in one of our European manufacturing sites.

​You will leverage your skills in data analysis, machine learning, software development, and deployment to systematically answer questions, provide actionable recommendations, and build robust data products. You will be responsible for modeling complex problems, discovering insights, and developing and deploying solutions.

Your main missions:

• Interpreting and analyzing data using statistical techniques and the scientific method.
• Formulating and leading multifaceted analytic studies against large datasets.
• Coordinating research and analytic activities, including data cleaning, manipulation, and organization.
• Analyzing problems and determining root causes.
• Translating complex results into clear conclusions and visualizations.
• Explaining sophisticated data science concepts in an understandable manner.
• Defining data assets, data models, and data pipelines.
• Working with business units to develop models and link results to processes.
• Coordinating with Data Engineers and deploying data environments.
• Experimenting with data, providing insights, and developing solutions.
• Developing, deploying, and maintaining data-driven applications and services.
• Building and managing APIs for data access and integration.
• Implementing and monitoring data pipelines and infrastructure.

Qualifications

• Bachelor’s, Master’s degree (preferred), or other advanced degree in computer science, business analytics, applied mathematics, statistics, machine learning, or data-centric discipline.
• 4+ years of relevant industry experience in advanced analytics and software development.
• Proficiency with multiple programming languages: Python, SQL.
• Expertise in Cloud and Big Data technologies would be a plus: Databricks, Google Cloud Platform
• Advanced analytics skills: descriptive statistical modeling, machine learning algorithms, data visualization, predictive analytics, and tools like Cognos, Graphana.
• Exceptional record of academic achievement, project management, and leadership.
• Strong software development and DevOps experience, including building and deploying applications.
• Advanced analytical knowledge of data, big data analysis, and data conditioning.
• Experience in core analytic methods like predictive modeling and segmentation.

Additional Information

We offer:

• structured integration and development of your skills
• competitive remuneration
• flexibility in the workplace 
• development opportunities including internationally

For more information on our Diversity & Inclusion approach, please click on this link: https://www.averydennison.com/en/home/about-us/diversity-and-inclusion.html