Business Lead — Boston, MA

Business Lead, AI-native Discovery Automation & Robotics

Location: Boston, Massachusetts, United States(Hybrid)

Industry: Pharmaceutical Manufacturing

Work Setting: Hybrid

This is a senior leadership role focused on transforming pharmaceutical drug discovery through the integration of AI, laboratory automation, robotics, data platforms, and scientific workflows. The position acts as the business owner of Takeda's Discovery Automation & Robotics product portfolio, driving the vision, strategy, adoption, and business value of AI-native laboratory orchestration platforms.

Key Responsibilities

• Define and own the vision, roadmap, and strategy for AI-driven laboratory orchestration and automation platforms.

• Lead the development of next-generation automated laboratory capabilities supporting 24/7 drug discovery operations.

• Partner with technical teams, product developers, automation engineers, and scientists to deliver business outcomes.

• Establish KPIs and measure adoption, scientific impact, operational efficiency, and business value.

• Drive cross-functional alignment across Research, Digital, Data, Technology, Computational Science, and external partners.

• Identify opportunities where AI agents, predictive models, robotics, and automation can improve experimental execution.

• Guide technology direction and architecture decisions while focusing on business objectives and scientific value.

• Lead change management and adoption initiatives across laboratory and scientific teams.

Required Qualifications

• Ph.D. in Engineering, Chemistry, Biology, Laboratory Automation, or a related field.

• 10+ years of experience in pharmaceutical or biotech R&D.

• Proven ownership of complex products, platforms, or technology portfolios.

• Strong experience in laboratory automation, robotics, high-throughput experimentation, or laboratory operations.

• Hands-on coding background with the ability to engage effectively with software, AI, data science, and engineering teams.

• Experience leading large transformation programs and influencing stakeholders across matrix organizations.

• Strong understanding of AI/ML, data platforms, scientific software, and automation technologies.

Preferred Experience

• ELN/LIMS platforms.

• Instrument scheduling and control systems.

• Scientific data platforms and sample tracking systems.

• AI-enabled discovery platforms.

• Digital twins and laboratory scheduling concepts.

• AI-ready scientific data architectures and metadata standards.