Business Lead, AI-native Large Molecule / Biologics Discovery

Scorpion Therapeutics; Boston (MA); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Takeda is seeking a Business Lead for its AI-native Large Molecule Discovery platform, responsible for defining and executing the product vision, strategy, and adoption within biologics research. Based in Cambridge, MA, hybrid work setup.

Responsibilities include owning the portfolio of AI-enabled discovery capabilities, aligning with scientific workflows, setting KPIs, and driving cross-functional prioritization across discovery, data science, and digital teams.

Qualifications

• Requires a PhD and 10+ years in pharma/biotech R&D with proven portfolio leadership.
• Demonstrated ability to set strategic technology directions across discovery and digital functions.
• Experience collaborating with scientists and external partners to deliver measurable impact.

Responsibilities

• Own the portfolio of AI-enabled biologics discovery capabilities and define KPIs.
• Drive cross-functional prioritization across discovery, data science, and digital teams.

Skills

Strategic product leadership

Portfolio management

Cross-functional collaboration

AI/ML in biologics

Education

PhD in computational biology, protein engineering, structural biology, or related field

Job description

Business Lead for Takeda’s AI-native Large Molecule Discovery platform, responsible for defining and executing the product vision, strategy, and adoption within biologics research.

Responsibilities: own the portfolio of AI-enabled biologics discovery capabilities, align with scientific workflows, set strategic direction, define KPIs, and drive cross-functional prioritization across discovery, data science, and digital teams. Collaborate closely with internal scientists and external partners to ensure capability development delivers measurable scientific and business impact, focusing on AI-driven workflows for large molecule design, engineering, and automation.

Requirements: Ph.D. in computational biology, protein engineering, structural biology, or related field; 10+ years in pharma/biotech R&D, with proven experience managing product portfolios, setting strategic technology directions, and working across discovery and digital functions. High-Value: expertise in biologics discovery, AI/ML applications in protein/antibody design, developability prediction, and automation platforms; experience with scientific software and AI-enabled discovery tools; stakeholder management in matrixed environments.

WorkSetup: based in Cambridge, MA, hybrid model.