below marketmost similar roles pay hereabove market
This role pays less than
95%
of similar roles. Most pay
$194,358–$259,460
— the blue band above.
At the midpoint, this role pays about
$148k
versus about
$227k
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.
The Scientific AI Platform Expert will join the Disease Area X Data Science team to build enterprise-grade AI analysis platforms and data products designed to accelerate drug discovery. This role involves leading multidisciplinary project teams to operationalize generative and agentic AI solutions while shaping the AI data strategy. Key responsibilities include designing and sustaining scalable omics pipelines, APIs, and integrated data products using FAIR data practices. The successful candidate will utilize technologies including Python, SQL, PyTorch, and deep learning frameworks. Expertise in LLM patterns, biological foundational models, and agent orchestration is preferred, alongside experience with Snowflake, Databricks, Palantir Foundry, and AWS. The role solves complex scientific problems by translating operational AI needs into decision-enabling solutions within a biopharma research context.
Translate scientific and operational AI needs into impactful, decision-enabling solutions.
Design, build, and sustain scalable AI-focused omics pipelines, APIs, and integrated data products.
Scale AI workflows using reproducible, transparent, secure, and FAIR data practices.
Operationalize generative and agentic AI solutions to accelerate drug discovery.
Shape the Disease Area X AI data strategy and prioritize resources against research needs.
Provide input on project evaluation, deployment, lifecycle, and governance practices.
Assist with the onboarding of external vendors and service providers.
Present strategy, implementation details, and results through technical documentation and publications.
What we're looking for
BS or MS in AI/ML, data science, computational biology, bioinformatics, computer science, mathematics, physics, or a related discipline.
3+ years of hands-on experience in scientific data science, engineering, or AI/ML within the biopharma or technology industry.
Qualified recent PhD graduates within the last 2 years will be considered.
Deep practical experience in software or data engineering including Python, SQL, version control, testing, workflow orchestration, cloud platforms, and data lakes.
Experience building and operating production-grade multimodal data platforms for scientific analysis.
Experience with omics analysis pipelines, MCP, LLM patterns, biological foundational models, agent orchestration, and Pytorch is preferred.
Familiarity with agentic frameworks such as Claude Science, Biomni, Gemini, or other open-source co-scientist platforms is preferred.
Demonstrated record of scientific or technical impact through publications, conference proceedings, open-source contributions, patents, or deployed data products.
Python
R
scikit-learn
SQL
Hive
SparkSQL
NLP
Machine Learning
ETL
Linux
Statistical Modeling
Clustering
Classification
Regression
Decision Trees
Support Vector Machines
Anomaly Detection
Recommender Systems
Large Language Models
LLM Post-training
SFT
DPO
RLHF
RFT
GRPO
Reward Modeling
Reinforcement Learning
PyTorch
Python
Generative AI
Agentic AI
ML Frameworks
LLM Evaluation