[Remote] Data Scientist - Materials R&D - Remote-Travel

Note: The job is a remote job and is open to candidates in USA. IPG is a global leader in packaging and protective solutions, committed to innovation and sustainability. They are seeking a Senior Data Scientist to support R&D in bio-polymers and sustainable materials by applying advanced data science and machine learning to enhance material performance and accelerate innovation.

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
• Experience working with batch or streaming data processes a plus
• 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

Skills

• Bachelor's degree in Data Science, Computer Science, Statistics, Materials Science, Chemical Engineering, or a related field
• 10+ years of professional experience in data science, applied analytics, or scientific computing
• 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
• Master's or PhD
• Experience working with materials science, polymer science or chemical R&D data
• Familiarity with bio‑polymers, sustainable materials, or polymer processing
• Experience with DOE software, laboratory data management systems (LIMS), or scientific databases
• Experience deploying models to support R&D decision-making or manufacturing scale-up
• Familiarity with cloud platforms (e.g., AWS, Azure) and data science lifecycle tools
• Prior experience mentoring or leading technical projects

Benefits

• Competitive pay
• Extensive benefits that support you and your family
• Exciting career development opportunities
• Ongoing training and the support you need to succeed

Company Overview

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