Senior Data Scientist — Materials R&D (Remote/Travel)

Itape; Marysville (MI); Remote; USD 120,000 - 180,000; Full time

Job summary

IPG is seeking a Senior Data Scientist to advance bio-polymers and sustainable materials through advanced data science, statistics, and ML. You will collaborate with polymer scientists, chemists, and engineers to accelerate development cycles and improve material performance.

The role supports R&D data workflows, DOE design, and scalable analytics across experimental and process data, with remote and travel requirements as needed.

Qualifications

• Bachelor’s degree in a related field; Master’s or PhD preferred.
• 10+ years of experience in data science or scientific computing, with materials/polymer R&D data preferred.
• Strong proficiency in Python and/or R for data analysis and modeling.

Responsibilities

• Partner with scientists and engineers to support bio‑polymer R&D using data-driven methods.
• Analyze and model experimental, formulation, and process data to identify structure–property–process relationships.
• Develop predictive models for material performance, design formulation screening, and process optimization.
• Design and analyze DOE experiments to maximize learning and reduce timelines.
• Build and maintain reproducible data workflows for ingestion, cleaning, and analysis.
• Apply ML techniques to complex scientific datasets and communicate insights clearly.

Skills

Python

R

SQL

Statistics

Experimental design

Multivariate analysis

Machine learning

Communication skills

Cross-functional collaboration

Data visualization

Education

Bachelor’s degree in Data Science / CS / Statistics / Materials Science / Chemical Engineering

Master’s or PhD preferred

Tools

DOE software

LIMS

Cloud platforms (AWS / Azure)

Job description

IPG is seeking a Senior Data Scientist to advance bio-polymers and sustainable materials through advanced data science, statistics, and ML. You will collaborate with polymer scientists, chemists, and engineers to accelerate development cycles and improve material performance.

The role supports R&D data workflows, DOE design, and scalable analytics across experimental and process data, with remote and travel requirements as needed.