Hybrid Data Scientist: Healthcare Data & Modeling

Solventum; Eagan, Northern (MN, KY); Hybrid; USD 106,000 - 146,000; Full time

Benefits offered by this job

Relocation assistance

Hybrid work eligible

Job summary

Solventum is hiring a Data Scientist in Eagan, MN, hybrid role. You will develop machine learning and statistical models on chemical/material datasets to improve formulation design and product performance. You will design data pipelines and collaborate with R&D and business teams to translate research into data-driven solutions.

The role requires advanced degrees with quantitative modeling focus and experience with Python. Occasional travel and a hybrid work arrangement are expected.

Qualifications

• Ph.D. or higher in a STEM field with emphasis on quantitative modeling or data science.
• MS in Data Science with a relevant Bachelor's degree and 1 year data science experience OR Bachelor's + 5 years experience in data science/informatics.
• Experience developing ML or predictive modeling solutions using Python and scientific computing libraries.

Responsibilities

• Develop machine learning and statistical models from chemical, materials, and experimental data.
• Integrate experimental and simulation-generated data to accelerate decision making.
• Design and maintain data pipelines, workflows, and analytical tools for reproducible analyses.
• Collaborate with R&D and business teams to translate research challenges into data-driven solutions.
• Communicate results to both technical and non-technical stakeholders.

Skills

Machine learning

Python

Data modeling

Statistical analysis

Chemical data science

Education

PhD in Chemical Engineering / Chemistry / Materials Science / Computational Chemistry / Data Science

MS in Data Science with related Bachelor's in Chemical Engineering / Chemistry / Materials Science

Bachelor's in Chemical Engineering / Chemistry / Materials Science

Tools

Python libraries

Job description

Solventum is hiring a Data Scientist in Eagan, MN, hybrid role. You will develop machine learning and statistical models on chemical/material datasets to improve formulation design and product performance. You will design data pipelines and collaborate with R&D and business teams to translate research into data-driven solutions.

The role requires advanced degrees with quantitative modeling focus and experience with Python. Occasional travel and a hybrid work arrangement are expected.