Senior Data Scientist

IPG's R&D team is advancing bio-polymers and sustainable materials through data-driven science. The Senior Data Scientist will apply advanced analytics, statistical modeling, and machine learning to experimental, process, and materials data to accelerate discovery, improve material performance, and reduce development cycles. This role is based in Marysville, Michigan with remote work options.

Responsibilities

• Collaborate with polymer scientists, chemists, and engineers to drive bio polymer R&D using data-driven methods.
• Analyze and model experimental, formulation, and process data to uncover structure–property–process relationships.
• Build predictive models to optimize material performance and properties.
• Develop models to guide formulation design and screening.
• Create models to support scale-up and process optimization.
• Design and analyze design-of-experiments studies to maximize learning efficiency and shorten development timelines.
• Create and maintain reproducible data workflows for R&D data ingestion, cleaning, and analysis.
• Apply machine learning methods such as regression, classification, clustering, and time-series modeling to complex scientific data.
• Collaborate with data engineering and IT teams to enable scalable R&D data infrastructure.
• Present insights, tradeoffs, and recommendations clearly to technical and non-technical stakeholders.
• Apply data visualization best practices to convey findings effectively.
• Experience with batch or streaming data processes is 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 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 with materials science, polymer science, or chemical R&D data is 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 (AWS, Azure) and data science lifecycle tools preferred.
• Prior experience mentoring or leading technical projects preferred.

Technologies

• Python
• R
• SQL
• AWS
• Azure
• LIMS
• DOE software

Benefits

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