Senior Manager, Oncology Data and AI Systems

Senior Manager, Oncology Data and AI Systems

Data, Data Science and Artificial Intelligence team (DDSAI) – Oncology R&D.

Location:

On site at Spring House, PA;
Cambridge, MA;
Titusville, NJ;
Raritan, NJ; or San Diego, CA (no fully remote option).

• Serve as both a people leader and a hands‑on contributor accountable for the end‑to‑end design, development, and operation of scalable, AI‑enabled data products supporting Oncology R&D.
• Drive integration of diverse data sources (biomarker labs, real‑world data, pre‑clinical and translational systems) into high‑quality, reusable, AI‑ready assets.
• Partner closely with Oncology R&D and Data Science stakeholders to shape, prioritize, and deliver against business‑critical use cases.
• Translate complex scientific and operational needs into robust data products and AI systems that accelerate decision‑making, improve study execution, and enhance probability of success.
• Collaborate with domain experts (ontology, knowledge graph, and data product engineering) to design and deliver future‑proof, AI‑ready data systems aligned with Oncology Strategy.
• Ensure solutions enable discoverability, reuse, and advanced analytics/GenAI applications.
• Implement standard enterprise‑level data models and create new data models as needed.
• Leverage cloud‑based technology platforms to achieve data and AI goals.
• Lead design and optimization of data pipelines and AI workflows for structured and unstructured data using Python, SQL, AWS services and other relevant tools.
• Mentor and onboard new team members.
• Implement quality and performance standards and measure KPIs to determine accuracy and consistency.
• Lead the team in the development of Agile practices and agentic AI coding tools.
• Act as a thought leader across Data Science, Engineering, and Oncology domains, ensuring alignment with broader data product strategy and avoiding duplication through reuse and standardization.

• Advanced degree (Master’s or equivalent) in Computer Science, Engineering, Life Sciences, or related field (Bachelor’s with equivalent experience may be considered).
• 6+ years of experience in data engineering, including data modeling and database design, preferably in the healthcare industry.
• Proficiency in agentic AI coding tools (e.g., Claude Code, Codex, etc.).
• Proficiency in data engineering tools such as Python and SQL for data processing, and 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 multidisciplinary and remote partners.
• Demonstrated stakeholder management capabilities – including requirements gathering, business analysis, and planning.
• Capacity to translate discussions into user requirements and project plans.
• Ability to manage multiple projects simultaneously, prioritize work, and exhibit organizational skills and flexibility to deliver maximum business value.
• Will travel