Data Scientist – Materials R&D

🔥 1 minute ago

🚗 Michigan – Remote

🚗 Michigan – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

📊 Data Scientist

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IPG

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🏭 Manufacturing

🤝 B2B

🛍️ eCommerce

Manufacturing • B2B • eCommerce

IPG is a manufacturer and supplier of adhesive tapes, packaging films, protective packaging products and automated packaging machinery. Its product portfolio includes carton-sealing tapes (acrylic, hot-melt, water-activated), industrial tapes (duct, foil, masking), packaging films (stretch, shrink, VCI), protective cushioning and mailers, and automated equipment such as case sealers, palletizers and tape heads. IPG serves business customers across e-commerce fulfillment, general manufacturing, building & construction, aerospace and other industrial sectors.

📋 Description

• Support R&D efforts in bio-polymers and sustainable materials by applying advanced data science, statistical modeling, and machine learning to data • Partner with polymer scientists, chemists, and engineers for bio‑polymer research • Analyze and model experimental data to identify structure–property–process relationships • Develop predictive models for material performance and property optimization • Design and analyze experiments to maximize learning efficiency • Build and maintain reproducible data workflows for R&D data • Apply machine learning techniques to complex scientific datasets • Collaborate with data engineering and IT teams for scalable data infrastructure • Communicate insights and recommendations clearly to stakeholders • Mentor junior data scientists and contribute to best practices in R&D • Stay current with advances in materials informatics and applied AI

🎯 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 • Familiarity with bio‑polymers, sustainable materials, or polymer processing, 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