Data Scientist – Materials R&D

🕒 August 10

🚗 Michigan – Remote

🚗 Michigan – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

📊 Data Scientist

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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 advanced data science, statistical modeling, and machine learning • Partner with polymer scientists, chemists, and engineers on bio-polymer research and development • Analyze and model experimental, formulation, and process data to identify structure–property–process relationships • Develop predictive models for material performance, formulation design, scale-up, and process optimization • Design and analyze experiments to maximize learning efficiency and reduce development timelines • Build and maintain reproducible workflows for R&D data ingestion, cleaning, and analysis • Apply machine learning techniques including regression, classification, clustering, and time-series modeling • Collaborate with data engineering and IT teams on scalable R&D data infrastructure • Communicate insights, tradeoffs, and recommendations 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 R&D data science best practices • 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 required; Master's or PhD preferred • 10+ years of professional experience in data science, applied analytics, or scientific computing • Experience 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 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 and 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 for R&D decision-making or manufacturing scale-up preferred • Familiarity with cloud platforms such as AWS or Azure and data science lifecycle tools preferred • Prior experience mentoring or leading technical projects preferred