Data Scientist – Materials R&D

🕒 6 days ago

🚗 Michigan – Remote

🚗 Michigan – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

📊 Data Scientist

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IPG

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🏭 Manufacturing

🏗️ Construction

🛍️ eCommerce

Manufacturing • Construction • eCommerce

IPG is a manufacturer and supplier of adhesive tapes, packaging materials, protective packaging products and automated packaging machinery. The company’s offerings span industrial tapes (duct, foil, flatback, filament, polyethylene), water-activated and carton-sealing tapes, packaging films (stretch, shrink, VCI), protective cushioning and mailers, geomembrane and building-envelope products, and automated case sealers, tape heads and palletizing equipment. IPG serves industrial, construction, e-commerce and manufacturing customers with both consumer and B2B product lines and emphasizes sustainable packaging options.

📋 Description

• Support R&D efforts in bio-polymers and sustainable materials 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, and 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 • 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

🎯 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 • 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