Sr Scientist Biostatistics

Johnson & Johnson Innovative MedicineLeidenHybridFull-time2 weeks ago

Johnson & Johnson is seeking a Senior Scientist in AI and Biostatistics to develop trustworthy, validated AI-enabled statistical solutions for pharmaceutical research and manufacturing. The role combines rigorous statistical thinking with hands-on AI development, including LLMs, RAG, and agentic workflows, in a regulated environment. Requires a PhD or Master's in a quantitative discipline and strong proficiency in R and/or Python.

What you'll do

Make statistical, mechanistic and predictive models accessible to AI workflows through documented interfaces and shared model services.
Build Python services and connect approved R and Python tools through APIs and Model Context Protocol (MCP).
Be accountable for the statistical integrity of AI-enabled solutions, ensuring appropriate treatment of variability, uncertainty, confounding factors and generalisability of findings.
Design, develop and deploy AI-enabled scientific applications that integrate statistical methods, machine learning, generative AI and domain knowledge into scalable and reusable solutions.
Develop agentic workflows that retrieve evidence, invoke scientific models and support interpretation and proposed next experiments.
Incorporate controlled tool execution, error handling and human review.
Prepare, curate and contextualise scientific data, experimental results and documents for AI applications.
Ensure appropriate treatment of data quality, metadata, provenance and uncertainty, and contribute to knowledge-graph and semantic-integration initiatives where relevant.
Collaborate with modelling and laboratory automation teams on iterative workflows that connect experimental results, model updates and experimental design while maintaining scientific rigour, traceability and governance.
Work with platform and security teams to deploy and operate applications, including access controls, configuration, logging, monitoring and validation.
Design end-to-end architectures for production scientific AI applications, covering user interfaces, services, APIs, data, models and deployment.
Define integration patterns that fit shared enterprise platforms.
Test applications and evaluate retrieval, tool use and generated outputs.
Work with domain experts to assess scientific validity, uncertainty and limitations, and investigate failures.
Contribute to the development of reusable statistical and AI capabilities across DMS, including documentation, software components, analytical frameworks, validation approaches, best practices and technical standards.
Serve as a scientific and technical thought leader by educating and mentoring statisticians and scientists in the effective application of AI, machine learning and modern computational methods.

What you need

Must-have

RPythonSQLGitMachine LearningGenerative AILarge Language ModelsRetrieval-Augmented Generation

Nice-to-have

ShinyQuartoFastAPIvLLMPosit WorkbenchPosit ConnectKnowledge GraphsCausal Inference

Soft skills

CollaborationCritical ThinkingCommunicationMentoringThought Leadership

BiostatisticsArtificial IntelligencePharmaceutical ManufacturingSenior ScientistMachine LearningGenerative AIRPythonHybridLeiden

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Nice-to-have

Soft skills

What you'll do

What you need