This role pays less than
78%
of similar roles. Most pay
$176,587–$256,850
— the shaded band above.
At the midpoint, this role pays about
$171k
versus about
$217k
for comparable roles.
Based on 240 similar postings.
Employer
About Johnson & Johnson
Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices
Johnson & Johnson currently has
61 open roles
on FindRole.
Listed pay typically runs
$117,000–$201,250
across 52 roles with salary data.
Principal Scientist, Applied AI, Immune Pathway Discovery joins the Immune Pathway Discovery team within Immunology Discovery to advance the discovery portfolio by applying human data and emerging technologies. This individual contributor role focuses on designing, building, and piloting AI-enabled solutions for high-value scientific use cases. The successful candidate will develop agentic workflows, scientific copilots, retrieval-augmented applications, and AI-assisted analytical tools while translating complex scientific needs into testable product hypotheses. Key responsibilities include executing technical plans, collaborating with discovery scientists to gather feedback, and transitioning validated prototypes into scalable capabilities. Required expertise includes a PhD in a relevant computational science field and proficiency in R or Python. The role requires experience with generative AI, large language models, and integrating various data sources while navigating security requirements. Essential skills include bioinformatics, advanced analytics, and high-dimensional biomedical data analysis.
Build and execute technical plans for AI prototypes across multiple scientific use cases.
Develop hands-on AI solutions including agentic workflows, scientific copilots, and retrieval-augmented applications.
Translate complex scientific needs into clear user requirements, testable hypotheses, and implementation plans.
Partner with scientists to gather feedback and iteratively improve AI-enabled tools.
Evaluate the accuracy, reliability, usability, and impact of AI solutions through rigorous testing.
Collaborate with engineering and data science teams to transition validated prototypes into scalable enterprise capabilities.
What we're looking for
PhD in a field relevant to artificial intelligence and computational science, such as Computer Science, Computational Biology, Bioinformatics, Biostatistics, Engineering, or Physics.
4+ years of relevant industry or applied research experience using computational methods to solve complex scientific or business problems.
Demonstrated experience building AI or machine learning solutions, prototypes, or research software in R or Python within modern software development environments.
Practical experience with generative AI, large language models, retrieval-augmented generation, agentic workflows, AI-assisted coding, or related technologies.
Experience integrating data sources, scientific tools, models, APIs, MCPs, or computational workflows while respecting governance and security requirements.
Proven ability to communicate and collaborate across scientific and technical disciplines with high scientific rigor.
Ability to independently formulate technical plans, troubleshoot complex systems, and manage multiple priorities to deliver usable outcomes.
Experience in pharmaceutical research, biotechnology, drug discovery, or other regulated scientific environments (preferred).
Data Science
Artificial Intelligence
Generative AI
Agentic Workflows
Python
R
SQL
Cloud Platforms
Machine Learning
Digital Health
Workflow Automation
Real-World Data
Imaging
Omics
Analytics
Data Platforms
Python
Machine Learning
Retrieval-Augmented Generation
Large Language Models
Data Engineering
OCI
knowledge-graph s
Data Pipelines
Statistical Analysis
Model Evaluation
Experimental Design
Bioinformatics
Genomics