Data Scientist - Materials R&D - Remote-Travel

This position can be based out of Marysville, MI, or work remotely with some travel as needed.Title: Senior Data ScientistDepartment: Research and DevelopmentStatus: Exempt Salaried

Position Purpose: The Senior Data Scientist will support R&D efforts in bio-polymers and sustainable materials and focusing on applying advanced data science, statistical modeling, and machine learning to experimental, process, and materials data to accelerate innovation, improve material performance, and reduce development cycles.

Principle Accountabilities

Partner with polymer scientists, chemists, and engineers to support bio‑polymer research and development using data-driven methodsAnalyze and model experimental, formulation, and process data to identify structure-property-process relationshipsDevelop predictive models to support:Material performance and property optimizationFormulation design and screeningScale‑up and process optimizationDesign and analyze experiments (DOE) to maximize learning efficiency and reduce development timelinesBuild and maintain reproducible data workflows for R&D data ingestion, cleaning, and analysisApply machine learning techniques (e.g., regression, classification, clustering, time-series modeling) to complex scientific datasetsCollaborate with data engineering and IT teams to enable scalable data infrastructure for R&DCommunicate insights, tradeoffs, and recommendations clearly to technical and non-technical stakeholdersUnderstanding of data visualization best practicesExperience working with batch or streaming data processes a plusContribute to data dictionaries and process flow diagrams for complex data solutionsMentor junior data scientists or technical staff and contribute to data science best practices within R&DStay current with advances in materials informatics, polymer modeling, and applied AI in scientific research

Essential Skills and Experience

Bachelor's degree in Data Science, Computer Science, Statistics, Materials Science, Chemical Engineering, or a related field; Master's or PhD preferred10+ years of professional experience in data science, applied analytics, or scientific computing; experience working with materials science, polymer science or chemical R&D data, preferredStrong proficiency in Python and/or R for data analysis and modelingSolid experience with SQL and working with structured and semi-structured datasetsStrong foundation in statistics, experimental design, and multivariate analysisDemonstrated experience applying machine learning to real-world, noisy scientific or experimental dataAbility to work effectively in a cross-functional R&D environmentStrong communication skills with the ability to translate complex analyses into actionable insightsFamiliarity with bio‑polymers, sustainable materials, or polymer processing, preferredExperience with DOE software, laboratory data management systems (LIMS), or scientific databases, preferredExperience deploying models to support R&D decision-making or manufacturing scale-up, preferredFamiliarity with cloud platforms (e.g., AWS, Azure) and data science lifecycle tools, preferredPrior experience mentoring or leading technical projects, preferred