3M, a global science and innovation leader, is seeking a Machine Learning/Vision Specialist - Process Data Scientist to join their team in Woodbury, Minnesota. This role presents an exciting opportunity to work at the intersection of data science, machine learning, and manufacturing processes.
The position offers a competitive compensation package ranging from $141,150 to $172,517, along with comprehensive benefits including medical, dental, and vision insurance. As a senior-level role, it requires at least 3 years of experience in machine learning and data science, with a strong focus on machine vision applications.
The successful candidate will be responsible for developing and implementing advanced algorithms, integrating diverse data sources, and driving technology adoption from laboratory to manufacturing settings. This role is perfect for someone who combines strong technical skills in Python and C++ with the ability to collaborate across teams and communicate complex technical concepts effectively.
Working at 3M means joining a company that values innovation and scientific collaboration. The role offers the opportunity to work on cutting-edge projects involving films, adhesives, and nonwovens, applying machine learning and vision techniques to improve manufacturing processes. The position requires on-site presence in Woodbury, MN, with up to 10% domestic travel.
The ideal candidate will have a bachelor's degree or higher in a relevant field, though advanced degrees are preferred. They should have demonstrated expertise in machine learning, data science, and machine vision, with experience in industrial data analysis and programming. The role offers growth opportunities within 3M's technical community through consulting and teaching.
This position is ideal for someone who wants to make a significant impact in a global manufacturing environment while working with cutting-edge technology. The role combines the stability of a well-established company with the excitement of working on innovative solutions to complex manufacturing challenges.