This role pays more than
77%
of similar roles. Most pay
$202,331–$275,080
— the shaded band above.
At the midpoint, this role pays about
$278k
versus about
$239k
for comparable roles.
Based on 239 similar postings.
Employer
About Novartis
Novartis is a global biopharmaceutical company that researches, develops, manufactures, and markets prescription drugs in areas including oncology, immunology, neuroscience, and cardiology. Industry: Biopharmaceuticals
Novartis currently has
26 open roles
on FindRole.
Listed pay typically runs
$194,600–$361,400
across 26 roles with salary data.
As Global Clinical Operations AI Product Director, you will join the team to translate complex business challenges into scalable Artificial Intelligence solutions that improve productivity and cycle times across clinical development. You will be responsible for identifying high-value AI opportunities, defining use cases, and managing products through the entire lifecycle from concept and MVP to pilot, refinement, and sustained adoption. The role requires bridging the gap between business stakeholders and technical teams while ensuring all solutions comply with GxP requirements and privacy guardrails. Key competencies include product management, digital delivery, and experience with Agile or Scrum methodologies. You will work with technologies including Machine Learning, Deep Learning, and model lifecycle concepts to solve problems in a highly regulated life sciences environment, specifically focusing on the automation and optimization of clinical trial operations and drug development workflows.
Artificial Intelligence
Machine Learning
Deep Learning
Data Science
Data Governance
Low-code
Process Automation
Clinical Operations
Good Clinical Practice (GCP)
Biostatistics
Graph Algorithms
Data Visualization
Change Management
Project Management
Program Management
Machine Learning
Large Language Models
Generative AI
Natural Language Processing
Python
SQL
Deep Learning
Model Evaluation
Clinical Data
EMR Systems
Data Science
Responsible AI
HIPAA
Artificial Intelligence
Machine Learning
Deep Learning
Data Science
Data Platforms
UX Principles
Agile
Data Visualization
Statistical Analysis
Time Series Analysis
Data Governance
Analytics