ML-Powered Data Scientist for Drug Discovery

BioSpace; North Chicago (IL); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Paid time off

Medical insurance

401(k)

Job summary

AbbVie is seeking a scientist to conceive and implement novel experimental approaches, identify predictive methods for protein targets, and optimize pharmacological properties. You will collaborate across science disciplines to advance project goals and develop robust computational tools for drug discovery.

The role emphasizes communication of model rationale, rigorous benchmarking, and deploying ML/ cheminformatics solutions with Python and modern libraries in a collaborative environment.

Qualifications

• Bachelor's or equivalent in relevant field with 7+ years experience; Master's with 5+ years.
• Thorough theoretical and practical understanding of own scientific discipline.

Responsibilities

• Consult with project team to establish quantitative targets for driving optimization.
• Identify models to predict small molecule binding affinities and pharmacological properties.
• Build predictive models and benchmark performance and domain applicability.
• Select appropriate model for each query molecule using data-driven approaches.
• Communicate rationale for model selection to project team.

Skills

Python

Machine Learning

Deep Learning

Cheminformatics

Cloud Computing

GNN/GCNN/MPNN

Data Analysis

Model Evaluation

Education

Bachelor's degree in chemistry / computer science / machine learning / cheminformatics / chemical engineering

Master's degree in relevant field

Tools

NumPy

Pandas

scikit-learn

Cloud platforms

Job description

AbbVie is seeking a scientist to conceive and implement novel experimental approaches, identify predictive methods for protein targets, and optimize pharmacological properties. You will collaborate across science disciplines to advance project goals and develop robust computational tools for drug discovery.

The role emphasizes communication of model rationale, rigorous benchmarking, and deploying ML/ cheminformatics solutions with Python and modern libraries in a collaborative environment.