Executive Director, Molecular Design Technology; BI&T

Position: Executive Director, Molecular Design Technology (BI&T)
Working with Us

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Role Overview

Bristol Myers Squibb is seeking a leader to serve as Executive Director, Molecular Design Technology-a pivotal role at the intersection of drug discovery science and advanced digital capabilities.

This global leader will define and deliver the technology strategy and capabilities that enable modality-agnostic molecular design and optimization across the R&D pipeline, in deep partnership with Research leadership spanning small molecules, biologics, and emerging modalities. The scope is explicitly focused on modality-agnostic design and optimization and excludes target identification and validation.

Reporting to the Vice President of Research Business Insights & Technology (BI&T), this individual will accelerate the shift from technology layered onto traditional workflows to computationally based, AI-driven ways of working. In partnership with research scientists, Computational Sciences leaders, and BMS's R&D Data organization, the role will advance a multi-year vision for integrated AI, data, and systems-ensuring design data and knowledge flow seamlessly across Research and into Development.

As a member of the BI&T leadership team, this leader will serve as a trusted partner to Research leaders to align priorities, roadmaps, and adoption across the organization.

Mission & Impact

* Set a cohesive, modality-agnostic technology and AI strategy for molecular design and optimization across Research.

* Deliver an integrated design ecosystem that reduces fragmentation and enables interoperable workflows, tools, and data.

* Enable scalable adoption of AI/ML, modeling & simulation, and generative design within scientists' day-to-day work.

* Establish closed-loop, data-driven design capabilities that improve learning speed and decision quality across the candidate lifecycle.

* Translate Research strategy into a prioritized, measurable roadmap-aligning leaders across Chemistry, Biology, and Computational Sciences.

* Drive change management and operating-model shifts so new capabilities are used consistently and deliver measurable impact.

Key Responsibilities

* Own the end-to-end technology strategy and roadmap for molecular design and optimization across modalities (small molecule, biologics, and emerging).

* Align priorities and drive delivery in close partnership with Discovery Biology, Medicinal Chemistry, Computational Sciences, and lab leadership.

* Select and scale core platforms and tools for structure-based design, modeling & simulation, AI/generative design, and design-workflow visualization.

* Architect and deliver an integrated design ecosystem (interoperable tools, datasets, and workflows) to reduce fragmentation and improve usability.

* Deliver measurable outcomes (e.g., DMTA cycle-time reduction; closed-loop optimization) through AI/ML, generative, and agentic capabilities.

* Own compound and entity registration systems and workflows, partnering with the R&D Data organization on the registered-entity data product.

* Ensure operational excellence (reliability, performance, support, and governance) for design platforms and integrated applications.

* Connect upstream Research with downstream Development (e.g., CMC and Manufacturing IT) so Development learnings flow back into design decisions.

* Build and lead a high-performing organization (talent, culture, performance) and manage external partnerships (vendors, startups, academic collaborators).

Required Experience & Qualifications

* Ph.D. in Chemistry, Computational Chemistry, Structural Biology, Bioinformatics, or related field

* 15+ years of experience in drug discovery, with:

* Deep experience in molecular design (small and/or large molecule)

* 10+ years operating at the intersection of science and technology/IT

* Proven track record of leading technology-enabled transformation in a pharmaceutical or biotech R&D environment

* Demonstrated experience implementing or scaling:

* Molecular modeling platforms

* AI/ML-driven drug design capabilities

* Integrated scientific data environments

* Strong understanding of end-to-end drug discovery workflows, particularly within design and optimization phases

*…