Senior Scientist, AI Lead

Johnson & Johnson

. Lead cross-functional AI projects supporting Cell & Gene Therapy development priorities .

Posted 10/12/2026full-timeMalvern • Pennsylvania • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading cross-functional AI projects within Cell & Gene Therapy, integrating AI solutions into scientific workflows, and translating complex scientific needs into actionable AI use cases. Proficient in evaluating model performance and ensuring responsible AI practices throughout the project lifecycle.

Highest-signal resume keywords

AI Solution ArchitectureMachine LearningNatural Language ProcessingProject ManagementBiotechnology Experience

ATS Keywords

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Hard Skills

PythonRDeep LearningGenerative AIPredictive AnalyticsKnowledge GraphsComputer VisionReinforcement LearningHybrid ModelingData Science

Soft Skills

Interpersonal SkillsCommunication SkillsStrategic InsightDetail OrientationCollaboration

Tools & Technologies

AI-Enabled Digital TwinsAutomated WorkflowsLaboratory Data IntegrationScientific Software

Industry Keywords

Cell & Gene TherapyPharmaceuticalsBiologics DevelopmentLife SciencesBiotechnology

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Lead cross-functional AI projects supporting Cell & Gene Therapy development priorities
Define project scope, plans, resources, milestones, decision points, and measurable success criteria
Coordinate cross-functional teams and external partners; manage risks, dependencies, decisions, and stakeholder communication
Lead the design, prototyping, testing, and iteration of AI solutions across machine learning, generative and agentic AI, natural language processing, computer vision, knowledge graphs, predictive analytics, and AI-enabled digital twins
Evaluate solutions for model performance, scientific validity, usability, reliability, and business value
Integrate successful solutions into scientific workflows, data platforms, digital twins, and automated laboratory environments
Embed responsible AI and lifecycle practices, including validation, transparency, privacy, security, governance, human oversight, performance monitoring, and communication of model limitations
Partner with process development, analytical, manufacturing, and business teams to identify challenges suitable for AI
Translate domain needs into AI use cases, user requirements, data needs, and expected outcomes
Assess use cases based on scientific value, business impact, data readiness, technical feasibility, risk, and scalability
Serve as an interface between scientific subject matter experts, data science, and technology teams
Establish relationships with internal data science teams, technology partners, academic collaborators, and vendors
Bring external developments and best practices into the organization
Contribute to the Cell & Gene Therapy AI roadmap
Define and track adoption, scientific impact, cycle-time, quality, and efficiency measures
Share outcomes, lessons learned, and reusable practices to accelerate organizational adoption
Promote AI adoption while preserving appropriate human judgment

Requirements

What you’ll need

A minimum of a BS degree in a core science or engineering field, including biology, chemistry, chemical/biochemical engineering, biomedical engineering, or a related discipline, with at least 4 years of relevant experience; OR an MS or equivalent with at least 2 years of relevant experience; OR a PhD or equivalent with 0–1 year of relevant experience
A minimum of 2 years of academic or industry experience delivering AI, machine learning, data science, or AI solution architecture initiatives
Experience applying AI approaches to pharmaceutical or life sciences problems preferred
Demonstrated experience leading complex projects from use-case definition through implementation
Working knowledge of supervised and unsupervised learning, deep learning, generative AI, large language models, agentic AI, natural language processing, computer vision, knowledge graphs, reinforcement learning, or hybrid modeling
Ability to translate scientific questions into AI solution requirements and technical outputs into actionable scientific or business decisions
Strong interpersonal and communication skills
Strategic insight, strong personal leadership skills, detail orientation, and effective collaboration with diverse team members
Hands-on experience developing or prototyping AI/ML solutions using Python, R, or comparable tools preferred
Experience with generative AI, retrieval-augmented generation, AI agents, multimodal models, or scientific knowledge graphs preferred
Experience with process modeling, mechanistic or hybrid modeling, predictive analytics, optimization, or AI-enabled digital twins preferred
Experience integrating AI with laboratory data, scientific software, connected equipment, or automated workflows preferred
Experience assessing model performance, data quality, explainability, limitations, and fit-for-purpose use preferred
Experience working in biotechnology, pharmaceuticals, Cell & Gene Therapy, biologics development, or a related scientific environment preferred
Willingness to undertake domestic and international travel up to 15%

Benefits

Comp & perks

Inclusive work environment
Equal opportunity employment
Interview process accommodations for applicants with disabilities
Domestic and international travel opportunities up to 15%