Principal Data Scientist – Oncology

Role Overview

• Be a key contributor to the design and implementation of a scalable knowledge graph infrastructure focused on data standardization and interoperability, focusing on Oncology R&D data.
• Apply graph-based data modeling for efficient Oncology R&D organization, integration and retrieval to ensure system flexibility and long-term maintainability.
• Work with a larger community of Data Scientists, Clinical Scientists, and Discovery Scientists to standardize, curate and create AI-Ready datasets.
• Curate and extend ontologies for clear mapping into established biomedical ontologies and controlled terminologies using resource description framework (RDF) standards.
• Work with SPARQL/GraphQL/REST services; develop ingestion and curation pipelines to ingest, normalize and map concepts across data sources.
• Extend and curate Oncology R&D-relevant ontologies (e.g., diseases, drugs, targets, pathways, etc.) and maintain synonyms, cross-references, and provenance.
• Partner with cross-functional teams to enable NLP/RAG over graphs, features for predictive modeling and terminology services for search and study design tools.
• Work with Data Science & Digital Health colleagues, IT and DevOps teams to deploy and manage the graph database infrastructure, focusing on high availability, scalability, and recovery operations specifically geared toward Oncology R&D needs and applications.
• Draft and manage documentation, such as data dictionaries, data lineage, and data flow diagrams, to facilitate understanding of the knowledge graph.

Requirements

• Desired Ph.D. or Master's degree in bioengineering, computer science, IT, bioinformatics, physics, mathematics, or related fields
• 5+ years professional experience in health informatics.
• Demonstrated experience in large-scale knowledge graphs construction, ontology development, pharmaceutical or healthcare domains integration.
• Programming background in parser combinators, natural language processing, and linked data (RDF Triple Stores and property graphs).
• Proficiency in semantic web technologies (e.g. SPARQL, RDF, OWL), familiarity with graph databases (Neo4j, Amazon Neptune).
• Proven work with complex biomedical datasets (e.g. clinical, genomics, proteomics).
• Proficiency in various data storage solutions (SQL, key-value, column, document, graph stores) and data modeling techniques (semantic data, ontologies, taxonomies).
• Experience in CI/CD implementations, git usage, CI/CD stacks (Jenkins, GitLab, Azure DevOps), DevOps tools, metrics/monitoring, and containerization technologies (Docker, Singularity).
• Demonstrated stakeholder management capabilities
• including requirements gathering, business analysis and planning.
• Must have the capacity to translate discussions into user requirements and project plans.
• Ability to manage a numerous projects simultaneously, prioritize work, exhibit organizational skills and flexibility to deliver maximum business value.

Tech Stack

• Azure
• Docker
• GraphQL
• Jenkins
• Neo4j
• SQL

Benefits

• Health insurance
• dental
• vision
• life insurance
• short
• and long-term disability
• business accident insurance
• group legal insurance
• consolidated retirement plan (pension)
• savings plan (401(k))
• Vacation – up to 120 hours per calendar year
• Sick time
• up to 40 hours per calendar year
• Holiday pay, including Floating Holidays – up to 13 days per calendar year of Work, Personal and Family Time
• up to 40 hours per calendar year