Chief Science Officer

About the role

The will own the scientific vision and execution of the platform's portfolio of AI-driven biotech programs. This role requires leading the evaluation, prioritization, and translation of multiple assets from concept to credible science. The CSO will act as the scientific anchor for the company, ensuring rigor and credibility in every initiative. They will attract, guide, and develop top-tier researchers to execute high-impact programs. This position is critical for bridging advanced AI outputs with real-world laboratory validation. The role demands deep expertise in drug development and regulatory pathways to de-risk the portfolio. Success will be defined by the quality and progress of scientific assets managed under this leadership.

Key facts

What you'll do

1. Own Bio's portfolio-level scientific direction by reviewing projects launching on Bio Protocol, maintaining a clear view of the pipeline, and making judgment calls on what to prioritize and what not to pursue.

2. Translate AI outputs into lab-validated science by working closely with Bio's AI team to convert AI-generated hypotheses into experimental validation and designing processes that turn computational insights into testable results quickly and rigorously.

3. Lead scientific diligence and evaluation by building scalable processes to assess scientific credibility, risk, and potential across projects and translating reviews into clear go/no-go recommendations for portfolio prioritization.

4. Recruit and support top-tier scientists by developing and executing a strategy to bring world-class researchers into Bio's ecosystem through academic networks, conferences, and partnerships while serving as a scientific sparring partner to refine hypotheses and stress-test approaches.

5. Represent Bio's scientific credibility externally by acting as the scientific voice with academics, biotech operators, investors, and ecosystem partners while staying current on scientific and biotech trends and representing Bio at conferences and industry events.

6. Build an AI-native scientific operating model by collaborating with Bio's systems and knowledge infrastructure to develop AI-driven workflows for research review, synthesis, and evaluation so that scientific judgment scales with the platform.

7. Lead and grow the science team by hiring, mentoring, and managing Bio's Science team to ensure the team operates at a high level and delivers on Bio's scientific mission.

8. Ensure meaningful exposure to the drug development and approval process by having observed programs through preclinical development, IND-enabling studies, clinical trials, and regulatory interaction to guide portfolio strategy with real-world insight.

9. Establish and maintain rigorous scientific review frameworks that align AI exploration with practical experimental feasibility and regulatory considerations.

10. Drive the creation of high-quality IP and de-risked assets that demonstrate clear commercial viability within the biotech and pharmaceutical landscapes.

11. Set standards for data integrity, experimental design, and reproducibility across all Bio-supported research initiatives.

12. Partner with the operations and business development teams to align scientific priorities with funding strategies and ecosystem growth.

13. Monitor competitive landscapes and technology trends to identify emerging opportunities and threats to Bio's portfolio objectives.

14. Provide thought leadership and strategic counsel to the executive team on scientific risks, timelines, and value creation pathways.

Requirements

A strong scientific foundation (PhD or equivalent depth) combined with experience outside of pure academia is essential for this role. This person must have meaningful exposure to the drug development and approval process, having witnessed one or more programs progress through preclinical development, IND-enabling studies, clinical trials, and regulatory interaction even if they were not directly executing the program. They should have senior scientific leadership experience, ideally with portfolio-level exposure in a biotech fund, a biotech company with multiple programs, or a similarly complex environment. A demonstrated understanding of drug development realities, regulatory risk, and translational challenges is required. The candidate must have a track record of attracting, advising, or leading researchers and scientific teams while operating comfortably at a strategic level and staying close to the science. An interest in AI-native approaches to scientific work and the ability to integrate computational insights with experimental validation is mandatory.

Practical notes

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