WORKING WITH US

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RayzeBio, a Bristol Myers Squibb company, is a dynamic biotechnology company headquartered in San Diego, CA. The company is focused on improving survival of people with cancer by harnessing the power of targeted radioisotopes. RayzeBio is developing innovative drugs against targets of solid tumors. Led by a successful and experienced entrepreneurial team, RayzeBio aims to be the global leader in radiopharmaceuticals .
RayzeBio is seeking a Director, Enterprise Data Architecture & AI Solutions to architect, integrate, and scale data and AI capabilities supporting our mission to advance next-generation radiopharmaceuticals. This highly visible leadership role spans cross-functional teams-including Commercial, Medical Affairs, Clinical Operations, Early Development, and Manufacturing-with a sharp focus on harmonizing enterprise data architecture and accelerating the application of AI/ML for real-world impact.
The ideal candidate combines technical acumen with systems integration expertise and stakeholder savvy, enabling both near-term wins and strategic transformation across RayzeBio’s rapidly growing organization.
The candidate will collaborate with BMS and the BI&T team to ensure all initiatives are not duplicative and are leveraging BMS know how and capabilities as appropriate.
The selected candidate will be required to travel regularly to all three sites (San Diego, Indianapolis, and Princeton) collaborating with teams across RayzeBio and BMS, spending 30% of the time at one of these three sites.

Required Qualifications

• BS Degree
• Minimum 10+ years in data architecture, analytics platform design, or commercial data operations-ideally within biotech, pharma, or healthcare.
• Proven record designing and scaling cloud-native data platforms/data models in multifaceted settings (including early-stage or growth-phase companies).
• Experience driving requirements definition, collaborating with engineering, and integrating complex, heterogeneous data systems.
• Deep understanding of oncology or radiopharmaceutical data (commercial, clinical, medical, or R&D).
• Demonstrated ability to operate independently and prioritize in a lean, entrepreneurial environment.
• Strategic and systems-oriented, with a passion for building scalable solutions and driving cross-enterprise alignment.
• Energetic self-starter-comfortable managing uncertainty, setting priorities, and influencing senior stakeholders.
• Highly collaborative; able to synthesize diverse viewpoints and translate ambiguous needs into concrete data/AI roadmaps.
• Pragmatic communicator-adept at concise documentation, presenting actionable concepts, and driving stakeholder engagement

Preferred Experience

• Experience in oncology-driven biotech or pharma, especially pre-commercial/early commercial stage.
• Working familiarity with life sciences regulatory frameworks (GxP, privacy, retention, commercial).
• Direct exposure to ML/AI in healthcare (predictive analytics, NLP, Gen AI, or decision support).
• Hands-on prototyping experience (Databricks, cloud notebooks, automation tools, etc.).
• Led or contributed to AI/ML/data platform initiatives within cross-functional/product teams

Enterprise Data Architecture & Platform Enablement

• Design, build, and continuously improve RayzeBio’s data lakehouse architecture to unlock analytics, reporting, and AI for enterprise users.
• Develop enterprise data models and semantic layers tailored for radiopharmaceutical workflows, enabling scalable self-service analytics and operational insights.
• Define integration strategy across enterprise applications (clinical, ERP, CRM, manufacturing, compliance) balancing traceability, integrity, and regulatory requirements.

Applied AI/ML Solution Design

• Identify and evaluate high-value opportunities for AI/ML in early development, clinical operations, supply chain, commercial analytics, and scientific knowledge management.
• Lead solution design for practical AI/ML pilots-coordinating in-house or external partners, ensuring alignment with RayzeBio’s digital and enterprise standards.
• Establish data readiness protocols for machine learning (annotation, pipeline integration, model monitoring/feedback, and secure deployment).

Enterprise Systems Integration & Scale-Up

• Own enterprise systems integration, dataflow design, and harmonization as RayzeBio transitions from pre-commercial to commercial-stage operations.
• Implement master data management solutions supporting unified product, customer, clinical trial, and manufacturing data domains.
• Collaborate with platform engineering, infrastructure, and partner teams to maximize interoperability and leverage best-in-class/reusable assets.

Governance, Quality, & Compliance

• Lead metadata management, master data governance, and stewardship processes-ensuring alignment with GxP, privacy, and commercial compliance requirements.
• Set and monitor high standards for data quality, system validation, and audit-readiness in collaboration with business and technical stakeholders.
• Champion cross-functional data governance (ownership, access, lineage) in a highly regulated, complex data ecosystem.

Stakeholder Leadership & Team Growth

• Serve as strategic advisor on data, analytics, and AI readiness-supporting business, R&D, and executive teams with actionable architectural guidance.
• Influence and align cross-functional partners toward shared goals and enterprise data priorities; champion ‘digital-first’ and Gen AI-enabled innovations.
• Establish and maintain strong relationships with BMS stakeholders
• Recruit, onboard, and mentor a small, high-impact team as RayzeBio scales.

Required Qualifications

• BS Degree
• Minimum 10+ years in data architecture, analytics platform design, or commercial data operations-ideally within biotech, pharma, or healthcare.
• Proven record designing and scaling cloud-native data platforms/data models in multifaceted settings (including early-stage or growth-phase companies).
• Experience driving requirements definition, collaborating with engineering, and integrating complex, heterogeneous data systems.
• Deep understanding of oncology or radiopharmaceutical data (commercial, clinical, medical, or R&D).
• Demonstrated ability to operate independently and prioritize in a lean, entrepreneurial environment.
• Strategic and systems-oriented, with a passion for building scalable solutions and driving cross-enterprise alignment.
• Energetic self-starter-comfortable managing uncertainty, setting priorities, and influencing senior stakeholders.
• Highly collaborative; able to synthesize diverse viewpoints and translate ambiguous needs into concrete data/AI roadmaps.
• Pragmatic communicator-adept at concise documentation, presenting actionable concepts, and driving stakeholder engagement.

Preferred Experience

• Experience in oncology-driven biotech or pharma, especially pre-commercial/early commercial stage.
• Working familiarity with life sciences regulatory frameworks (GxP, privacy, retention, commercial).
• Direct exposure to ML/AI in healthcare (predictive analytics, NLP, Gen AI, or decision support).
• Hands-on prototyping experience (Databricks, cloud notebooks, automation tools, etc.).
• Led or contributed to AI/ML/data platform initiatives within cross-functional/product teams.