Principal Data Scientist, R&D Oncology

Principal Data Scientist, R&D Oncology

Data Science and Digital Health team (DSDH) position, located in Spring House, PA (preferred), Cambridge, MA or San Diego, CA (La Jolla area). Consideration may be given to Titusville, NJ and Raritan, NJ locations.

This role will support data capture, build and optimize data workflows and store data by designing and implementing engineering requirements. The focus is on Oncology R&D and will support data projects across Clinical, Pre‑Clinical, RWD and ‘omics platforms. It is a leading technical contributor and creative problem solver developing AI‑ready data and other routinely used data applications for Oncology R&D.

• Design, develop and maintain data pipelines for acquiring, managing and storing Oncology R&D data from diverse sources (e.g., biomarker labs, real‑world data sources, pre‑clinical applications)
• Work closely with Data Science and Oncology R&D partners to understand, document and prioritize business requirements. Translate these business needs into high‑quality data products.
• Work closely with other technical leaders such as Ontology and Knowledge Graph Engineers to design and deliver future‑proof, AI‑ready data systems aligned with Oncology R&D business needs.
• Develop Oncology R&D‑specific data repositories by implementing standard enterprise‑level data models and create new data models as needed. Leverage cloud‑based technology platforms to accomplish goals, such as building and maintaining data repositories using AWS S3.
• Create and optimize data flows for structured and unstructured data using technologies such as Python, R, SQL, AWS services and other relevant tools.
• Implement quality and performance standards and measure KPIs to determine accuracy and consistency.
• Leverage and implement data versioning and lineage tracking to support data traceability, compliance, and maintaining documentation for data architectures and workflows.
• In adherence to internal standards, implement software development best practices such as code versioning and Dev Ops.

• Advanced degree (Master’s or equivalent) in Computer Science, Engineering, Life Sciences, or other relevant field is strongly preferred. (Bachelor’s Degree with experience equivalency may be considered.)
• 3+ years of experience in data engineering, including data modeling and database design, preferably in the healthcare industry.
• Proficiency in data engineering tools such as Python, R and SQL for data processing as well as cloud architecture (e.g., AWS services, Redshift, FSx, Glue, Lambda).
• Experience with unstructured database technologies (e.g., No
  
  SQL) as well as other database types (e.g., Graph).
• Strong skills in analysis, problem‑solving, organizational change, project delivery and managing external vendors.
• Proven record leading improvement initiatives with multi‑disciplinary and remote partners.
• 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 numerous projects simultaneously, prioritize work, exhibit organizational skills and flexibility to deliver maximum business value.
• Willingness to conduct periodic travel (