Data Scientist - Materials R&D - Remote-Travel
About The Position
The Senior Data Scientist will support Research and Development efforts in bio-polymers and sustainable materials. The role applies advanced data science, statistical modeling, and machine learning to experimental, process, and materials data to accelerate innovation, improve material performance, and reduce development cycles. The position can be based in Marysville, Michigan, or performed remotely with travel as needed. The role partners with polymer scientists, chemists, engineers, data engineering, and IT teams to develop data-driven solutions for R&D. It also contributes to reproducible data workflows, scalable R&D data infrastructure, clear communication of findings, and data science best practices. The position is salaried and exempt.
Requirements
- Bachelor’s degree in Data Science, Computer Science, Statistics, Materials Science, Chemical Engineering, or a related field.
- 10 or more 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 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.
Nice To Haves
- Master’s or PhD degree.
- 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 such as AWS or Azure and data science lifecycle tools.
- Prior experience mentoring or leading technical projects.
- Experience working with batch or streaming data processes.
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 for 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, including regression, classification, clustering, and 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 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.
Benefits
- Competitive pay.
- Extensive benefits that support employees and their families.
- Career development opportunities and ongoing training.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
