Principal Data Scientist: AI-Ready Life Sciences Data

Johnson and Johnson; United States; On-site; USD 170,000 - 240,000; Full time

Job summary

Johnson & Johnson is seeking a Principal Scientific Data Scientist to lead the design, implementation, and evolution of AI-ready data products for drug discovery and development. You will build scalable data products that connect discovery through real-world evidence and enable knowledge graphs, semantic reasoning, and GraphRAG across cross-functional teams.

The role requires a strong background in data architecture, cloud platforms, and data governance, with collaboration across scientists, AI

Qualifications

• Requires advanced degree in a relevant field and 5+ years in scientific data engineering or life sciences informatics.
• Experience delivering enterprise-scale scientific data products and data architectures.

Responsibilities

• Lead design and implementation of scalable scientific data products and integration strategies.
• Define data architecture and metadata framework supporting AI-ready assets.
• Architect interoperability across discovery, preclinical, clinical, safety, and real-world data.
• Drive AWS-based platform strategy and scalable data pipelines with platform teams.
• Collaborate with scientists, data strategists, and AI engineers to deliver data solutions.
• Ensure governance, security, and FAIR data principles across products.

Skills

Data architecture

Cloud-native platforms

Metadata management

Data governance

Predictive modeling

Python / R

Knowledge graphs

GraphRAG

AI readiness

Cross-functional collaboration

Education

Master's or PhD in Computer Science

Data Engineering or Biomedical informatics

Information systems or Computational biology

Tools

AWS-based data platforms

Data lakes / lakehouses

Data catalogs and lineage solutions

APIs / data services

Job description

Johnson & Johnson is seeking a Principal Scientific Data Scientist to lead the design, implementation, and evolution of AI-ready data products for drug discovery and development. You will build scalable data products that connect discovery through real-world evidence and enable knowledge graphs, semantic reasoning, and GraphRAG across cross-functional teams.

The role requires a strong background in data architecture, cloud platforms, and data governance, with collaboration across scientists, AI