Senior Manager, Oncology Data and AI Systems

About the role

The Senior Manager, Oncology Data and AI Systems will focus on building data and AI systems in Oncology R&D and support projects from across the business including Clinical, Pre-Clinical, Real World Data (RWD) and 'omics platforms.

Responsibilities

• 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 (e.g., 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, such as Ontology, Knowledge graph, and Data Product Engineers 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 accomplish data and AI goals.
• Lead the design and optimization of data pipelines and AI workflows for structured and unstructured data using technologies such as Python, SQL, AWS services and other relevant tools.
• Mentor and on-board new team members.
• Implement quality and performance standards and measure Key Performance Indicators (KPIs) to determine accuracy and consistency.
• Lead 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.

Requirements

• 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).
• 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 as well as cloud architecture (e.g. AWS services, Redshift, FSx, Glue, Lambda.).
• Experience with unstructured database technologies (e.g. NoSQL) 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.
• Ability to manage numerous projects simultaneously, prioritize work, exhibit organizational skills and flexibility to deliver maximum business value.
• Willingness to conduct periodic travel (