IPG

Data Scientist - Materials R&D - Remote-Travel

Marysville, MI, USPosted 1 day ago

Job Description

Join the IPG Team!

Are you ready to elevate your career? At IPG, we are more than just a global leader in packaging and protective solutions—we are a community that values safety, people, passion, integrity, performance, and teamwork. From tapes and films to packaging and protective products, as well as engineered coated materials and advanced packaging machinery, we develop innovative solutions that protect the world. Now, we are expanding our global team and looking for talented individuals like you!

This position can be based out of Marysville, MI, or work remotely with some travel as needed.

Title

Senior Data Scientist

Department

Research and Development

Status

Exempt Salaried

Position Purpose

The Senior Data Scientist will support R&D efforts in bio-polymers and sustainable materials and focusing on applying advanced data science, statistical modeling, and machine learning to experimental, process, and materials data to accelerate innovation, improve material performance, and reduce development cycles.

Principle Accountabilities

  • Partner with polymer scientists, chemists, and engineers to support bio polymer research and development using data-driven methods
  • Analyze and model experimental, formulation, and process data to identify structure–property–process relationships
  • Develop predictive models to support:
  • Material performance and property optimization
  • Formulation design and screening
  • Scale up and process optimization
  • Design and analyze experiments (DOE) to maximize learning efficiency and reduce development timelines
  • Build and maintain reproducible data workflows for R&D data ingestion, cleaning, and analysis
  • Apply machine learning techniques (e.g., regression, classification, clustering, time-series modeling) to complex scientific datasets
  • Collaborate with data engineering and IT teams to enable scalable data infrastructure for R&D
  • Communicate insights, tradeoffs, and r

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