Jobs at Johnson & Johnson

Leads strategic and operational execution of clinical biomarker and diagnostic plans across complex drug development studies. Oversees biospecimen lifecycle management, laboratory vendors, assay readiness, data delivery, budgets, risks, quality, regulatory compliance, and audit readiness. Partners with cross-functional teams, drives process improvements, manages stakeholders and external partners, and provides mentorship or matrix leadership across global programs.

Leads the architecture and engineering evolution of J&J MedTech’s global Microsoft Dynamics marketing platform. Defines shared services, APIs, SDKs, developer frameworks, reusable AI agents, interoperability standards, observability, security, and platform operations. Partners with product, business, and AI teams to scale governed AI-driven commercialization capabilities across marketing and related commercial functions. Establishes engineering metrics, standards, and organizational capabilities while leading modernization initiatives and engineering teams in a complex, regulated enterprise environment.

Leads the technical strategy, roadmap, architecture, delivery, reliability, governance, and lifecycle management of J&J MedTech’s global marketing platform. Translates business needs into technology investments, coordinates internal teams and vendors, manages budgets and risks, drives Agile delivery, and ensures cybersecurity, compliance, operational continuity, and measurable business value across the Microsoft Dynamics ecosystem.

Leads development and deployment of integrated spatial omics, functional genomics, and massively parallel reporter assay platforms for therapeutic discovery. Designs perturbation libraries, reporter assays, cellular models, spatial profiling workflows, and screening campaigns. Establishes laboratory capabilities, evaluates emerging technologies, manages collaborators and CROs, and partners with computational scientists to translate complex multiomic datasets into biological insights and therapeutic hypotheses.

Leads the vision, strategy, prioritization, lifecycle, delivery, operations, and value realization of MedTech customer experience marketing platforms. Manages platform roadmaps, technical backlogs, vendors, budgets, compliance, risk, architecture alignment, AI enablement, incident response, and continuous improvement. Partners globally with product, architecture, portfolio, engineering, and business teams while managing individual contributors and driving Microsoft Dynamics 365 platform outcomes.

Develops, optimizes, validates, and implements manufacturing processes, equipment, and controls in a regulated medical-device environment. Conducts process characterization, capability studies, DOE, data analysis, troubleshooting, and root-cause investigations. Supports new product introductions, equipment selection and qualification, process validations, continuous improvement, technical documentation, and compliance. Collaborates with Operations, Quality, Maintenance, Engineering, Supply Chain, and vendors to improve quality, efficiency, safety, and cost performance.

Leads systems engineering for a safety-critical surgical robotic platform across its full lifecycle. Defines system architecture, requirements, interfaces, risk controls, verification strategies, and design controls. Coordinates hardware, software, controls, mechanical, clinical, quality, manufacturing, and V&V teams. Supports regulatory submissions, reliability engineering, design transfer, product launches, failure investigations, CAPA, and post-market activities while applying MBSE and UML methods.

Leads portfolio strategy, governance, planning, resource management, executive reporting, and analytics for technology, data, and AI initiatives in R&D. Builds dashboards, data models, automated reporting workflows, and portfolio intelligence to support prioritization and investment decisions. Partners with leadership and project teams to improve governance, data quality, reporting consistency, risk management, and value realization.

Develop and validate AI/ML models for translational safety prediction, biomarker discovery, mechanistic inference, and clinical outcomes across discovery, preclinical, clinical, and real-world data. Integrate multimodal biological and healthcare datasets, advance foundation models and AI reasoning, establish scientifically credible and regulatory-ready validation, and collaborate with pharmaceutical, safety, data engineering, and external teams to operationalize models for R&D decisions.

Leads systems engineering for orthopedic robotic and surgical navigation platforms. Responsibilities include requirements management, system-level risk analysis, architecture development, subsystem integration, interface management, verification and validation, sustaining engineering, regulatory submission support, and compliance with medical device standards. The role collaborates with hardware, electrical, software, marketing, and testing teams and coaches engineers on systems engineering practices.

Leads a multidisciplinary systems engineering team developing safety-critical surgical navigation platforms. Owns system architecture, requirements flow-down, interface management, risk management, design controls, verification traceability, and regulatory compliance. Partners with hardware, software, controls, mechanical, clinical, quality, manufacturing, and V&V teams across the product lifecycle. Drives design reviews, reliability, usability, root-cause investigations, product launch, regulatory submissions, and technical decision-making while developing team members and supporting project planning.

Lead product cybersecurity for connected heart-recovery medical devices across development and post-market lifecycles. Responsibilities include security architecture, threat modeling, risk assessments, cryptographic controls, secure boot, firmware protection, PKI, vulnerability management, penetration testing, SBOM analysis, secure OTA updates, regulatory submissions, and remediation planning. The role partners with R&D and cross-functional teams to implement secure development practices, embedded protections, cloud and device security, and compliance with medical-device cybersecurity standards.

Conduct research developing multimodal AI and machine learning systems for biomedical discovery and drug development. Integrate imaging, omics, molecular, literature, and clinical data to generate biological insights, identify disease mechanisms, and prioritize targets or compounds. Responsibilities include model development, benchmarking, scientific software creation, experimental collaboration, documentation, publications, and communication of findings across multidisciplinary teams.

Conduct advanced AI/ML research for drug discovery and therapeutic design, developing foundation models, generative models, and representation learning methods for biological sequences. Integrate AI-guided design with wet-lab validation, analyze complex biological datasets, collaborate across computational and experimental teams, communicate findings, maintain code repositories, and publish research in leading conferences and journals.

Supports pharmaceutical R&D through clinical pharmacology and pharmacometrics activities, including literature review, PK/PD data analysis, trial design, model building, simulation, population modeling, quantitative systems pharmacology, model-based meta-analysis, data visualization, and machine learning. Interns collaborate with multidisciplinary teams across preclinical and clinical development programs in multiple therapeutic areas.

Supports biostatistical design, analysis, interpretation, and reporting for clinical development, medical affairs, discovery, and manufacturing programs. Uses R, SAS, Python, and advanced statistical methods to guide study designs, simulations, sample size calculations, regulatory submissions, and data communications. Collaborates with cross-functional teams, CROs, and regulatory stakeholders; ensures reproducible, compliant deliverables and contributes to publications, process improvements, and statistical methodology advancement.

Lead and execute Real-World Evidence (RWE) studies end-to-end: design, data feasibility, extraction, cleaning, statistical analysis, programming, and interpretation. Develop shared tools and best practices, mentor team members, produce protocols and analysis-ready deliverables, and support regulatory interactions alongside therapeutic area scientists.

Build and maintain agentic AI workflows that automate secondary biologics discovery analysis and connect laboratory automation, scientific data, models, and compute environments. Develop real-time or near-real-time pipelines, resilient APIs, observability, versioning, and orchestration. Partner with discovery scientists, AI/ML teams, data engineers, GenAI platform teams, and MLOps colleagues to enable closed-loop DMTL feedback, high-quality traceable data, and production-ready scientific automation.

Leads data science, AI, digital health, and analytics strategy for Immunology R&D. Partners with scientific, clinical, platform, and engineering teams to identify use cases, analyze workflows, evaluate emerging technologies, develop scalable solutions, and improve research execution and decision-making. The role focuses on healthcare, imaging, clinical, biomarker, real-world, and digital health data, including generative and agentic AI applications.

The Principal Data Scientist - Oncology will lead efforts in standardizing and connecting biomedical and clinical data through the development of scalable knowledge graph infrastructure and AI-Ready datasets.