AI Lead Scientist, Biologics Process Development

BioSpace; North Chicago (IL); On-site; USD 150,000 - 230,000; Full time

Job summary

AbbVie is implementing an AI-native team focused on early-stage biologics, data science, and advanced analytics to accelerate development and regulatory-ready decisions. You will embed AI into pipelines, build predictive models, and partner with scientists to drive faster, safer, and cost-effective biologics programs.

You will lead the design of hybrid modeling, ensure data governance under GxP, and contribute to cross-functional strategy with process scientists, engineers, and quality leaders.

Qualifications

• Hands-on data science or ML development in a scientific/engineering setting.
• Expert-level Python with strong ecosystem support (NumPy, pandas, scikit-learn, PyTorch or TF).
• Experience with DoE, Bayesian methods or active learning in scientific apps.
• Familiarity with MLOps, model lifecycle management, and GxP/regulatory needs.
• Proven ability to communicate complex analyses to non-technical stakeholders.

Responsibilities

• Develop, validate, and deploy predictive models for early-stage biologics.
• Design hybrid modeling to balance physics-based and data-driven approaches.
• Build analytical frameworks for digital twins and in-silico optimization.
• Define data strategies across experiments and ensure data quality and traceability.
• Translate analyses into actionable insights for cross-functional decision makers.

Skills

Python proficiency

NumPy

pandas

scikit-learn

PyTorch

TensorFlow

R

Dataiku

AWS SageMaker

Spark

Tableau

DoE

Bayesian methods

active learning

GxP/regulatory experience

Education

Bachelor's degree in computer science or related field

MS or PhD in Data Science, Biostatistics, Computational Biology, or related

Tools

Dataiku

AWS SageMaker

Spark

Tableau

Job description

AbbVie is implementing an AI-native team focused on early-stage biologics, data science, and advanced analytics to accelerate development and regulatory-ready decisions. You will embed AI into pipelines, build predictive models, and partner with scientists to drive faster, safer, and cost-effective biologics programs.

You will lead the design of hybrid modeling, ensure data governance under GxP, and contribute to cross-functional strategy with process scientists, engineers, and quality leaders.