Director, AI Nexus for Drug Development Decisions

Bristol Myers Squibb; Princeton (NJ); On-site; USD 225,000 - 272,000; Full time

Benefits offered by this job

Comprehensive benefits

Flexible Time Off

Retirement benefits

Job summary

Bristol Myers Squibb seeks a Director, Drug Development AI Nexus Decision Integration Lead to bridge Drug Development, Research and the AI Nexus team. You will translate strategic priorities into AI-enabled workflows, governance, and data requirements to improve decision quality and speed.

Positioned in Drug Development Excellence, this role collaborates with BI&T, GPTs, and leaders to drive adoption and implement agentic, AI-native approaches across R&D.

Qualifications

• Senior leadership experience bridging science, operations and technology.
• Ability to translate business requirements into AI-enabled workflows and governance.
• Strong cross-functional collaboration and influence across GPTs and governance bodies.
• Experience driving adoption of new operating models and change management.

Responsibilities

• Translate strategic priorities into scalable AI-enabled workflows and data requirements.
• Act as Drug Development anchor for the AI Nexus platform within GPTs and governance forums.
• Redesign key decision points to leverage AI Nexus-enabled evidence and learning loops.
• Partner with BI&T and Platform Engineering to ensure platform alignment with needs.
• Serve as embedded translator between Drug Development needs and AI Nexus capabilities.

Skills

Drug Development

AI Nexus

Stakeholder Engagement

Change Leadership

Tools

AI Nexus Platform

Platform Engineering

BI&T

Job description

Bristol Myers Squibb seeks a Director, Drug Development AI Nexus Decision Integration Lead to bridge Drug Development, Research and the AI Nexus team. You will translate strategic priorities into AI-enabled workflows, governance, and data requirements to improve decision quality and speed.

Positioned in Drug Development Excellence, this role collaborates with BI&T, GPTs, and leaders to drive adoption and implement agentic, AI-native approaches across R&D.