Principal Data Scientist, Immunology

Johnson & Johnson

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Titusville, NJCambridge, MARaritan, NJSpring House, PASan Diego, CA
Salary: $117,000–$201,250 / yr
Posted: 116 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $177k

This role $159k

$104k most similar roles pay here $238k

This role pays less than 65% of similar roles. Most pay $140,000–$213,817 — the shaded band above. At the midpoint, this role pays about $159k versus about $177k for comparable roles.

Based on 240 similar postings.

Employer

About Johnson & Johnson

Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices

Johnson & Johnson currently has 46 open roles on FindRole.

Listed pay typically runs $117,000–$201,250 across 42 roles with salary data.

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At a glance

TL;DR · Principal Data Scientist, Immunology

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Principal Data Scientist - Immunology joins the Immunology R&D Data Science & Digital Health team to serve as a technical contributor focused on knowledge graph engineering. The role involves designing and implementing scalable infrastructure to standardize and connect biomedical and clinical data across the product lifecycle. Key responsibilities include developing ingestion pipelines, curating ontologies for diseases and drugs, and creating AI-ready datasets to power analytics and search tools. The position requires expertise in semantic technologies, RDF standards, SPARQL, GraphQL, and REST services, alongside experience with graph databases like Neo4j or Amazon Neptune. Candidates must possess skills in natural language processing, data modeling, and CI/CD workflows using tools like Docker and Jenkins. This role addresses the critical challenge of ensuring interoperable knowledge for immunology research by integrating complex datasets including clinical, genomic, and proteomic information into a unified system.

What does a Data Scientist earn in California?

Median $208978 from 66 postings across 27 companies.

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Skills

Knowledge Graphs RDF SPARQL OWL Neo4j Amazon Neptune GraphQL REST SQL NLP RAG Docker Singularity Git CI/CD Jenkins GitLab Azure DevOps Data Modeling

What you'll do

Design and implement a scalable knowledge graph infrastructure for Immunology R&D data standardization and interoperability.
Apply graph-based data modeling to organize, integrate, and retrieve complex immunology research data.
Curate and extend biomedical ontologies using RDF standards to map diseases, drugs, targets, and pathways.
Develop ingestion and curation pipelines to normalize and map concepts across diverse data sources using SPARQL, GraphQL, or REST.
Partner with cross-functional teams to enable NLP/RAG over graphs and provide features for predictive modeling.
Collaborate with IT and DevOps teams to deploy and manage high-availability graph database infrastructure.
Create technical documentation including data dictionaries, lineage, and flow diagrams to facilitate system understanding.

What we're looking for

A Ph.D. or master's degree in bioengineering, computer science, IT, bioinformatics, physics, mathematics, or a related field is preferred.
5+ years of professional experience in health informatics is preferred.
Experience in large-scale knowledge graph construction and ontology development within pharmaceutical or healthcare domains is preferred.
Proficiency in semantic web technologies including SPARQL, RDF, and OWL is required.
Familiarity with graph databases such as Neo4j or Amazon Neptune is required.
Programming experience in parser combinators, natural language processing, and linked data (RDF Triple Stores and property graphs) is preferred.
Experience with various data storage solutions like SQL, key-value, column, and document stores is preferred.
Proficiency in CI/CD stacks, Git, Docker, or Singularity is preferred.

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