Principal Data Scientist, R&D Oncology

Job Title

Principal Data Scientist, R&D Oncology

Job Function:
Data Analytics & Computational Sciences
Job Sub Function:
Data Science
Job Category:
Scientific/Technology

Principal Data Scientist, R&D Oncology will support how we advance data capture, build and optimize data workflows and store data by designing and implementing engineering requirements. This role focuses on applications in Oncology R&D and supports data projects from across the business including Clinical, Pre-Clinical, RWD and “omics” platforms. This role will be a leading technical contributor and creative problem solver with 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 platform 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, maintaining documentation for data architectures and workflows.
• In adherence to internal standards, implement software development best practices such as Code Versioning, 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 (