Principal Data Scientist, AI/ML for Pharma Analytics

AbbVie Inc.; North Chicago (IL); On-site; USD 125,000 - 237,000; Full time

Job summary

AbbVie Analytical Research & Development (Analytical R&D) is seeking a Principal Research Scientist I to lead data-science efforts for analytical data, AI/ML, and automated data products in pharmaceutical development.

You will mentor scientists, drive end-to-end data products, and collaborate across global teams to translate complex data into actionable insights, ensuring scientific rigor and regulatory compliance.

Qualifications

• Bachelor’s, Master’s, or Ph.D. in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, Chemometrics, Computational Science, Analytical Chemistry, Pharmaceutical Sciences, or a closely related discipline, typically with years of relevant industry experience.
• Demonstrated experience applying data science, AI/ML, statistics, or advanced analytics to scientific or R&D problems.
• Advanced proficiency in Python and/or R with data-science libraries and reproducible workflows.

Responsibilities

• Provide scientific and technical leadership for analytical data science, AI/ML, advanced analytics, visualization, and data automation initiatives.
• Lead end-to-end delivery of data products including data acquisition, modeling, visualization, and deployment.
• Mentor data scientists and collaborate with analytical scientists, statisticians, and IT partners.
• Coordinate multiple projects, communicate progress to senior stakeholders, and promote reusable standards.

Skills

Python

R

Data science

AI/ML

Statistics

Git

SQL

Communication

Education

Ph.D. in Data Science

Ph.D. in Chemistry

Master’s in Statistics

Tools

Streamlit

Shiny

Git

SQL

Job description

AbbVie Analytical Research & Development (Analytical R&D) is seeking a Principal Research Scientist I to lead data-science efforts for analytical data, AI/ML, and automated data products in pharmaceutical development.

You will mentor scientists, drive end-to-end data products, and collaborate across global teams to translate complex data into actionable insights, ensuring scientific rigor and regulatory compliance.