Data Scientist

TOMRA Sorting Solutions serves the world’s most important recyclers with sorting solutions and services, and is expanding rapidly on a global scale. As part of our growth, we are actively driving the transition towards digitally enhanced customer solutions to achieve new levels of efficiency, quality and transparency.

Recycling plants are complex processes with a low level of digitalization and therefore a big optimization potential deploying state-of-the-art data driven technologies exists. As a Data Scientist will play a crucial role in advancing TOMRA Recycling's sensor-based sorting technology. This role involves analyzing vast amounts of data to enhance sorting algorithms, improve system efficiency, and support the development of innovative solutions for recycling and material recovery. The ideal candidate will have a strong background in data analysis, machine learning, and a passion for sustainability and environmental impact reduction.

Your task

• Analyze large datasets from sensor-based sorting systems to identify patterns, trends, and insights that can improve sorting efficiency and accuracy.
• Develop and refine machine learning algorithms to enhance the performance of sorting technologies, ensuring high precision in material identification and classification. This could be done by manipulating a sorter based on external data.
• Establish and maintain data pipelines, ensuring the integrity, quality, and accessibility of data from various sensor sources.
• Create comprehensive reports and visualizations to communicate findings, model performance, and insights to both technical, non-technical stakeholders as well as customers.
• Stay abreast of the latest developments in data science, machine learning, and recycling technologies by contributing to innovative projects, developing proof of concepts (POCs) and pilot studies.
• Collaborate with cross-functional teams including the R&D development team, product managers, and customers to develop holistic solutions.

Requirements

• Master's degree in Data Science, Computer Science, Engineering, or a related field.
• Proven experience (+3 years) in data analysis, machine learning, and statistical modeling.
• Proficiency in programming languages such as Python, R, or similar.
• Familiarity with big data technologies and tools (e.g., Hadoop, Spark).
• Strong analytical, problem-solving, and communication skills.
• Passion for sustainability and environmental conservation.