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Data Scientist Project Manager Jobs in Michigan (NOW HIRING)

... impactful projects in a dynamic team environment. As an AI/ML Data Scientist, you will be ... their manager}.This job may be eligible for relocation benefits. About GM Our vision is a world ...

... impactful projects in a dynamic team environment. As an AI/ML Data Scientist, you will be ... manager}. This job may be eligible for relocation benefits. About GM Our vision is a world with ...

Take ownership of projects, ensuring their successful planning, budgeting, execution, and ... The Opportunity As part of the Operations Consulting team, you will apply advanced data science and ...

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Data Scientist Project Manager information

What are the key skills and qualifications needed to thrive as a data scientist project manager?

To thrive as a Data Scientist Project Manager, you need a solid background in data science, analytics, and project management, often supported by degrees in computer science, statistics, or business and certifications like PMP or Agile. Familiarity with tools such as Python, R, SQL, project management software (e.g., Jira, Trello), and cloud platforms is crucial. Excellent communication, leadership, and problem-solving abilities help bridge gaps between technical teams and stakeholders. These skills ensure successful project delivery by aligning data-driven insights with business objectives and effective team coordination.

What is a data scientist project manager?

A Data Scientist Project Manager is a professional who oversees data science projects from conception through completion, ensuring that project goals align with business objectives. They bridge the gap between data science teams and stakeholders, managing timelines, resources, and communication. In addition to technical knowledge in data science and analytics, they possess strong project management skills to coordinate tasks, mitigate risks, and deliver results. Their role is essential for translating complex data-driven insights into actionable business strategies. They often use methodologies like Agile or Scrum to guide project workflows and adapt to changing requirements.

Can a data scientist become a data scientist project manager?

A data scientist can become a data scientist project manager by developing leadership, communication, and project management skills, often through experience and certifications like PMP or Agile. Transitioning typically involves gaining experience in managing projects and teams while maintaining technical expertise in data analysis and modeling.

What is the difference between Data Scientist Project Manager vs Data Analyst Project Manager?

AspectData Scientist Project ManagerData Analyst Project Manager
Required CredentialsBachelor's/Master's in Data Science, Analytics, or related fields; certifications like PMP or AgileBachelor's in Data Analysis, Business, or related fields; certifications like PMP or Agile
Work EnvironmentLeads data science projects, collaborates with data scientists and engineersManages data analysis projects, works with analysts and business teams
Employer & Industry UsageTech companies, finance, healthcare, industries with advanced analyticsRetail, marketing, finance, industries relying on data reporting

The main difference is that Data Scientist Project Managers oversee data science initiatives involving complex modeling and algorithms, while Data Analyst Project Managers focus on managing data reporting and analysis projects. Both roles require project management skills and relevant certifications, but their technical focus and team collaboration differ.

How do data scientist project managers typically balance technical data work with project management responsibilities?

Data Scientist Project Managers often split their time between hands-on data analysis and overseeing project progress. They commonly coordinate with cross-functional teams, set project timelines, and ensure that data solutions align with business objectives while occasionally contributing code or analytical insights. Effective communication and time management are essential, as they must bridge the gap between technical teams and stakeholders. This dual responsibility offers exposure to both technical growth and leadership development, making it ideal for professionals seeking advancement into higher management roles.
What are popular job titles related to Data Scientist Project Manager jobs in Michigan? For Data Scientist Project Manager jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Data Scientist Project Manager jobs? Cities in Michigan with the most Data Scientist Project Manager job openings:
Infographic showing various Data Scientist Project Manager job openings in Michigan as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Data Scientist - Materials R&D - Remote-Travel

Itape

Marysville, MI โ€ข On-site

$130 - $185/hr

Other

Posted 4 days ago


Job description

Data Scientist - Materials R&D - Remote-Travel

Marysville, MI 48040, USA

Job Description

Posted Saturday, July 11, 2026 at 4:00 AM

Join the IPG Team!

Are you ready to elevate your career? At IPG, we are more than just a global leader in packaging and protective solutionsโ€”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

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 bioโ€‘polymer research and development using data-driven methods
  • Analyze and model experimental, formulation, and process data to identify structureโ€“propertyโ€“process relationships
  • Develop predictive models to support:
    • Material performance and property optimization
    • Formulation design and screening
    • Scaleโ€‘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
  • Bachelorโ€™s degree in Data Science, Computer Science, Statistics, Materials Science, Chemical Engineering, or a related field; Masterโ€™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 bioโ€‘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 jobโ€”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.

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