Senior Data Scientist: Lab Automation & AI Solutions

NBMBAA; Maplewood, Northern (MN, KY); Hybrid; USD 146,000 - 178,000; Full time

Benefits offered by this job

Relocation assistance

On-site work (Maplewood, MN)

Job summary

3M is seeking a Senior Data Scientist to join our Maplewood, MN team on-site. You will identify digital science opportunities across laboratory automation and advanced digital products, develop predictive models, and collaborate with cross-functional teams to translate complex data into scalable solutions.

The role requires strong experience in data science, ML, and data engineering, with a track record of delivering impactful R&D outcomes and driving adoption of digital tools across labs.

Qualifications

• Bachelor’s degree or higher in science, math, or engineering (completed and verified prior to start)
• Five (5) years of experience in data science, statistical modeling, ML, simulation, or related work (including graduate research)

Responsibilities

• Identify and prioritize digital science opportunities accelerating innovation in lab automation, Forge, and RepairStack.
• Develop and validate predictive, statistical, ML, and simulation models for high-value challenges.
• Define data requirements, clean and organize data, and improve data quality and usability.
• Translate technical problems into scalable digital solutions and integrate models into workflows.
• Own pilots from identification to adoption, including milestones and governance.

Skills

Data science

Statistical modeling

Machine learning

Simulation

Numerical methods

Data engineering

Education

Bachelor’s degree or higher in science/math/engineering

Master’s degree or Ph.D. in a relevant technical discipline

Tools

Cloud

MLOps

Workflow integration

Job description

3M is seeking a Senior Data Scientist to join our Maplewood, MN team on-site. You will identify digital science opportunities across laboratory automation and advanced digital products, develop predictive models, and collaborate with cross-functional teams to translate complex data into scalable solutions.

The role requires strong experience in data science, ML, and data engineering, with a track record of delivering impactful R&D outcomes and driving adoption of digital tools across labs.