VP, Head of Drug Discovery in Cambridge

The Opportunity: We are seeking an exceptional scientific leader to oversee our integrated Medicinal Chemistry, Computational Chemistry, Cheminformatics, and Drug Metabolism & Pharmacokinetics (DMPK) organizations. This individual will be responsible for driving the discovery and optimization of transformative small molecule therapeutics by building a highly collaborative, data-driven discovery engine that combines deep scientific expertise with modern computational approaches.

The successful candidate will be a recognized leader in small molecule drug discovery with a proven track record of advancing programs from hit identification through IND filing. They will be a key member of research leadership, fostering an environment where all disciplines work as a unified team to rapidly test hypotheses, learn from experimental data, and deliver differentiated medicines. This role is ideal for a leader who is energized by solving complex scientific problems, embracing emerging technologies, and building high-performing scientific organizations within a fast-paced biotechnology environment.

We believe breakthrough medicines emerge from the seamless integration of human creativity, rigorous experimentation, and advanced computational science. Our discovery strategy combines hypothesis-driven biology, medicinal chemistry, computational chemistry, structural biology, and DMPK to iteratively design, test, and refine molecules based on quantitative experimental evidence. By coupling deep scientific expertise with state-of-the-art computational technologies, we aim to accelerate learning, improve decision quality, and deliver differentiated therapies for patients with serious diseases.

Your Role:

• Scientific Leadership
• Lead and integrate the Medicinal Chemistry, Computational Chemistry, Cheminformatics, and DMPK organizations to create a highly effective, collaborative drug discovery engine.
• Define and execute scientific strategies that enable rapid progression from target validation to development candidate nomination.
• Champion hypothesis-driven drug discovery by integrating predictive computational methods and medicinal chemistry.
• Ensure that molecular design decisions are informed by a comprehensive understanding of potency, selectivity, physicochemical properties, ADME, safety, developability, and translational considerations.
• Drive scientific excellence through rigorous data analysis, critical thinking, and evidence-based decision making.
• Ensure efficiency and optimal resource utilization through integration of emerging technologies when appropriate.
• Organizational Leadership
• Build strong partnerships across biology, biomolecular sciences, translational medicine, and project leadership.
• Guide portfolio prioritization and resource allocation.
• Create an environment where multidisciplinary teams operate with shared objectives and transparent communication.
• Remove organizational barriers that limit collaboration and ensure efficient decision-making across discovery functions.
• Work across functions to ensure successful project transitions into development.
• Innovation
• Drive adoption of technologies including AI/ML-enabled molecular design, structure-based drug design, molecular simulations, free-energy calculations, generative chemistry, predictive ADME models, cheminformatics, and high throughput experimentation.
• Promote rigorous evaluation of emerging technologies while maintaining strong emphasis on experimental validation.
• Ensure computational methods accelerate discovery through measurable scientific impact rather than technology adoption alone.

Your Background:

• Ph.D. in Organic Chemistry or Computational Chemistry.
• 15+ years of progressively increasing leadership responsibility in biotechnology and/or pharmaceutical drug discovery.
• Demonstrated success leading multidisciplinary discovery organizations.
• Proven track record of advancing multiple small molecule programs from target identification through development candidate nomination.
• Deep understanding of medicinal chemistry, molecular design, ADME/DMPK, structure-based drug design, and computational chemistry.
• Demonstrated success implementing modern computational approaches including AI/ML applications, molecular modeling, predictive property models, and data-driven discovery workflows into medicinal chemistry decision making.
• Experience with emerging modalities including heterobifunctional and other beyond rule of 5 approaches.
• Strong scientific publication record and recognition within the drug discovery community.
• Excellent communication and organizational leadership skills.