This role pays less than
84%
of similar roles. Most pay
$177,137–$241,789
— the shaded band above.
At the midpoint, this role pays about
$159k
versus about
$209k
for comparable roles.
Based on 240 similar postings.
Employer
About AbbVie
AbbVie is a global biopharmaceutical company focused on discovering and delivering innovative medicines and solutions in immunology, oncology, neuroscience, and eye care. Its products include Humira, Skyrizi, and Rinvoq.
AbbVie currently has
141 open roles
on FindRole.
Listed pay typically runs
$109,500–$208,500
across 131 roles with salary data.
Senior Scientist I - II, Computational HitGen / LeadGen joins the HGLG team to drive AI-enabled drug discovery across a small molecule portfolio. This role involves identifying, developing, and deploying innovative methods for computational hit generation while collaborating with medicinal chemists and structural biologists. The successful candidate will establish project-relevant criteria, select optimal methodologies, and develop workflows to predict binding affinities, design compounds with specific pharmacological properties, and sample both enumerated and AI-generated chemical spaces. Key responsibilities include evaluating synthetic tractability of designs from generative AI and communicating complex technical rationale to non-specialists. Required expertise includes machine learning, deep learning, cheminformatics, and Python programming. The role focuses on solving challenges in hit and lead generation by utilizing advanced computational tools for molecular design, pose prediction, and retrosynthetic analysis within an early-stage drug discovery context.
Cheminformatics
Data Science
Machine Learning
Artificial Intelligence
Python
SQL
Deep Learning
Generative AI
Linux
High-Performance Computing
Pandas
R
Data Visualization
Active Learning
Drug-Target Interaction Modeling
Free Energy Perturbation
Ligand Protein Docking
Python
PyTorch
JAX
Machine Learning
Deep Learning
Generative Modeling
Protein Language Models
Foundation Models
Geometric Neural Networks
AlphaFold
Active Learning
Multimodal Learning
Representation Learning
Data Integration
Design-Build-Test-Learn