Note: The job is a remote job and is open to candidates in USA. IPG is a global leader in packaging, protective solutions, engineered coated materials, and advanced packaging machinery. The Senior Data Scientist will support R&D in bio-polymers and sustainable materials by applying data science, statistical modeling, and machine learning to experimental, process, and materials data. The role focuses on accelerating innovation, improving material performance, reducing development cycles, and mentoring technical staff.
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 preferred
- Experience working with materials science, polymer science or chemical R&D data, preferred
- * 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 (e.g., AWS, Azure) and data science lifecycle tools, preferred
- * Prior experience mentoring or leading technical projects, preferred
Benefits
- Remote work option based out of Marysville, MI, with some travel as needed
- Extensive benefits that support you and your family
- Career development opportunities
- Ongoing training
- Support to enhance your skills or advance your career
- A safe, supportive workplace
- Cross-department collaboration
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