Position: Senior Scientist, AI Applications - R&D Oncology

Job Function

Data Analytics & Computational Sciences
Job Sub Function

Data Science
Job Category

Scientific/Technology
Job Location s

Cambridge, Massachusetts, United States;
New Brunswick, New Jersey, United States;
Raritan, New Jersey, United States;
San Diego, California, United States;
Spring House, Pennsylvania, United States
Job Description

Senior Scientist, AI Applications, R&D Oncology in the Data Science & Digital Health (DSDH) team (DSDH AI/ML). The position will be located in the Spring House PA (preferred), Cambridge MA, or San Diego CA (La Jolla area) offices; consideration may also be given to the Titusville and Raritan, NJ locations. No remote option.

The Senior Scientist will develop and deliver artificial intelligence (AI)/machine learning (ML) scientific applications for oncology drug discovery and development. The role involves working closely with Large Language Models (LLMs) and advanced data science techniques across large datasets that span scientific literature, omics, and biomolecular knowledge.
Key Responsibilities
• Hands‑on technical delivery of advanced AI/ML oncology R&D research.
• Translate business opportunities with Oncology R&D and Data Science leaders into research plans.
• Develop and optimize multimodal reasoning systems that integrate structured and unstructured data.
• Build novel agent memory architectures for persistent knowledge retention and context‑aware decision‑making.
• Prototype and evaluate approaches for uncertainty quantification and reliability assessment in AI‑driven scientific reasoning.
• Serve as a domain expert, communicating emerging AI/ML approaches to team members.
• Benchmark agent performance against expert decisions and publish results in leading journals and conferences.
• Define and enforce engineering best practices for AI prototyping, including architecture patterns, documentation standards, quality gates, and reproducibility criteria.
• Contribute to the overarching AI strategy, enabling scaling and deployment of tools for the broader R&D community.
Required Qualifications
• Ph.D. in AI/ML or related field (e.g., computer science, machine learning, data science, applied mathematics, statistics) with at least two years of related work experience.
• Strong knowledge of advanced mathematical concepts such as Bayesian inference, uncertainty quantification, information theory, causal inference, and graph neural networks.
• Proficiency with open‑source agentic frameworks (e.g., Lang Graph, DSPy, mem0) and deep learning frameworks (e.g., PyTorch, Tensorflow).
• Proficiency in one or more programming languages, preferably Python.
• Positive, motivated demeanor, capable of independent work and collaboration within a multidisciplinary team.
Preferred Qualifications
• Understanding of the drug discovery pipeline and familiarity with biological data types, with experience in oncology research.
• Strong understanding of statistics and methods required to validate model performance.
• Experience with cloud hosting solutions (e.g., AWS, Azure).
Compensation & Benefits

Base pay range: $109,000 to $174,800. Eligible for annual performance bonus and company‑sponsored benefits including medical, dental, vision, life insurance, short and long‑term disability, business accident insurance, group legal insurance, retirement plan (401(k)), and other benefits per local market.

Time off benefits:
Vacation up to 120 hours per calendar year;
Sick time up to 40 hours per calendar year;
Holiday pay including floating holidays up to 13 days per calendar year;
Work, personal and family time up to 40 hours per calendar year.
EEO Statement

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
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