below marketmost similar roles pay hereabove market
This role pays more than
74%
of similar roles. Most pay
$205,150–$281,262
— the blue band above.
At the midpoint, this role pays about
$278k
versus about
$243k
for comparable roles.
Based on 240 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
17 open roles
on FindRole.
Listed pay typically runs
$176,400–$327,600
across 17 roles with salary data.
JOB TITLE: Director, AI and Machine Learning for Biology
The Director, AI and Machine Learning for Biology will lead the US data science capability and shape the global AI strategy to accelerate target discovery. This leader will manage a high-performing team of applied AI, machine learning, computational biology, and data science professionals to build biological foundation models, multimodal learning, and biomedical knowledge graphs. Day-to-day responsibilities include defining a prioritized portfolio of AI initiatives, translating scientific questions into computational strategies, and integrating longitudinal human data, genetics, multi-omics, and imaging. The role requires expertise in Python, deep learning frameworks, and distributed computation to solve problems in human genetics, proteomics, and transcriptomics. The work focuses on uncovering causal drivers of aging, resilience, and regeneration to identify novel therapeutic targets for age-related diseases.
Shape and execute the global AI and machine learning strategy for the organization.
Define a prioritized portfolio of data science initiatives to accelerate target discovery and experimental design.
Lead the development of biological foundation models, multimodal learning, and biomedical knowledge graphs.
Translate complex scientific questions into specific computational strategies using machine learning and bioinformatics.
Build and lead a high-performing US-based team of data scientists and computational biologists.
Evaluate emerging technologies and establish external partnerships to enhance internal AI capabilities.
Drive the adoption of AI tools across the department to improve drug-discovery decisions.
What we're looking for
PhD in Machine Learning, Computational Biology, Data Science, Computer Science, Systems Biology, or a related quantitative discipline with a deep understanding of biology.
10+ years of experience applying advanced computational and AI approaches to biomedical research, drug discovery, or translational medicine.
Proven success leading multidisciplinary global teams across AI, human data, and experimental science.
Demonstrated experience developing or applying advanced machine-learning approaches to complex biological data, including foundation models and multimodal learning.
Strong working knowledge of deep learning, representation learning, multi-modal AI, generative AI, and large-scale biological data modeling.
Strong experience in large-scale model training, distributed computation, model adaptation, and deployment within machine learning operations frameworks.
Strong coding proficiency in Python and deep learning frameworks, with experience using version control systems.
Experience with omics data (transcriptomics, proteomics, metabolomics) and cellular imaging data.
Generative AI
LLMs
RAG
LangChain
LlamaIndex
Vector Databases
Prompt Engineering
Multi-agent Orchestration
Machine Learning
Data Science
Fine-tuning
Model Evaluation
AI Governance
Model Risk Management
Agile
Python
AWS
Spark
H2O
Scala
R
Conda
Machine Learning
Deep Learning
Time Series
Clustering
Classification
Sentiment Analysis
Big Data
Relational Database
Python
AWS
Spark
H2O
Scala
R
Conda
Machine Learning
Deep Learning
Time Series
Clustering
Classification
Sentiment Analysis
Big Data
Relational Database
Generative AI
Agentic AI
LLMs
Python
NLP
Retrieval
Grounding
Data Science
Medical Imaging
Multi-omics
Genetics
Genomics
Ontologies
AI Governance
Human-in-the-loop
Data Analytics
Artificial Intelligence
Machine Learning
Python
C++
AWS
Google Cloud
Microsoft Azure
Databricks
Snowflake
Data Engineering
Data Analytics
Data Infrastructure
Data Wrangling
GenAI