Data Scientist - Materials R&D - Remote-Travel

Intertape Polymer Group (IPG) • Marysville, MI

13d • Remote

About The Position

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.
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.

Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, Materials Science, Chemical Engineering, or a related field; Master’s or PhD preferred
• 10+ years of professional experience in data science, applied analytics, or scientific computing; experience working with materials science, polymer science or chemical R&D data, preferred
• Strong proficiency in Python and/or R for data analysis and modeling
• Solid experience with SQL and working with structured and semi-structured datasets
• Strong foundation in statistics, experimental design, and multivariate analysis
• Demonstrated experience applying machine learning to real-world, noisy scientific or experimental data
• Ability to work effectively in a cross-functional R&D environment
• Strong communication skills with the ability to translate complex analyses into actionable insights

Nice To Haves

• Experience working with batch or streaming data processes a plus
• Familiarity with bio‑polymers, sustainable materials, or polymer processing, preferred
• Experience with DOE software, laboratory data management systems (LIMS), or scientific databases, preferred
• Experience deploying models to support R&D decision-making or manufacturing scale-up, preferred
• Familiarity with cloud platforms (e.g., AWS, Azure) and data science lifecycle tools, preferred
• Prior experience mentoring or leading technical projects, preferred

Responsibilities

• 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 recommendations clearly to technical and non-technical stakeholders
• Understanding of data visualization best practices
• Contribute to data dictionaries and process flow diagrams for complex data solutions
• Mentor junior data scientists or technical staff and contribute to data science best practices within R&D
• Stay current with advances in materials informatics, polymer modeling, and applied AI in scientific research

Benefits

• We offer competitive pay, extensive benefits that support you and your family, and exciting career development opportunities.
• Whether you are looking to enhance your skills or advance your career, we offer ongoing training and the support you need to succeed.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level