Data Scientist - Materials R&D - Remote-Travel
Intertape Polymer Group (IPG)Marysville, MI • On-site, Remote
Full-time
Posted 13 days ago
Intertape Polymer Group rating
7.0
Based on 10 frontline employees who took The Breakroom Quiz
62nd of 109 rated packaging manufacturers
Job description
Are you ready to elevate your career? At IPG, we are more than just a global leader in packaging and protective solutions-we are a community that values safety, people, passion, integrity, performance, and teamwork. From tapes and films to packaging and protective products, as well as engineered coated materials and advanced packaging machinery, we develop innovative solutions that protect the world. Now, we are expanding our global team and looking for talented individuals like you!
This position can be based out of Marysville, MI, or work remotely with some travel as needed.
Title: Senior Data Scientist
Department: Research and Development
Immediate Supervisor: R&D Vice President
Status: Exempt Salaried
Position Purpose: The Senior Data Scientist willsupport 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 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
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 preferred
- 10+ years of professional experience in data science, applied analytics, or scientific computing; experience working with materials science, polymer science or chemical R&D data, 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 (e.g., AWS, Azure) and data science lifecycle tools, preferred
- Prior experience mentoring or leading technical projects, preferred
Why Choose IPG?
At IPG, you will find more than just a job-you will find a place where your success is our success. We pride ourselves on a culture built around strong relationships, where every team member plays a crucial role in our growth. Whether it is through cross-department collaboration, continuous training, or sustainability-driven initiatives, we create an environment where you can thrive.
Our commitment to sustainability influences everything we do, from designing eco-friendly products to minimizing waste in our production processes. We are dedicated to building a greener future while providing safe, supportive workplaces for our people.
With over 40 years of industry expertise and a proven track record of growth and innovation, IPG offers a stable, secure environment where you can flourish!
We offer competitive pay, extensive benefits that support you and your family, and exciting career development opportunities. Whether you are looking to enhance your skills or advance your career, we offer ongoing training and the support you need to succeed. Think big, dream bigger, and make an impact with IPG.
You belong here. Join us today!
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Scientist?
A: To succeed as a Data Scientist, one must possess core technical skills such as proficiency in programming languages like Python, R, or SQL, as well as expertise in machine learning algorithms, data visualization tools like Tableau or Power BI, and statistical modeling techniques. Additionally, strong soft skills like effective communication, collaboration, and problem-solving abilities, along with traits like curiosity, adaptability, and attention to detail, are crucial for success in this role. By combining these technical and soft skills, Data Scientists can effectively extract insights from complex data, drive business decisions, and drive career growth through continuous learning and innovation.
Q: What is the career path for a Data Scientist?
A: A Data Scientist's typical career progression involves starting as a Junior Data Analyst or Data Scientist, where they develop foundational skills in data analysis, machine learning, and visualization. As they gain experience, they can move into mid-level roles such as Senior Data Scientist or Lead Data Analyst, where they take on more complex projects, mentor junior team members, and contribute to strategic decision-making. Ultimately, senior Data Scientists can transition into leadership positions like Director of Data Science or Chief Data Officer, or pursue specialized roles like Data Engineering or Artificial Intelligence Research Scientist, depending on their interests and skills.
