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Bio Protocol

Chief Science Officer

Reposted One Month Ago
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Remote
Hiring Remotely in USA
Senior level
Remote
Hiring Remotely in USA
Senior level
The Chief Science Officer will direct Bio's scientific agenda, ensure comprehensive evaluation of research initiatives, lead talent acquisition in science, and enhance the drug development process using AI-driven methodologies.
The summary above was generated by AI

Bio is a decentralized science protocol that helps launch and grow AI-driven biotech research. It enables scientists to raise funds, create value from their work, and distribute that value directly to their communities. Since 2023, Bio has directed over $50m to global researchers, offering an alternative to traditional pharma funding. Backed by investors like Binance Labs, Northpond Ventures, and Animoca Brands, Bio accelerates real-world therapeutics across longevity, brain health, fertility, psychedelic science, and more.

Why this role exists

Bio is entering a phase where scientific ambition must deliver repeatable, credible outcomes at portfolio scale. We need senior leadership to evaluate, prioritize, and support multiple assets while improving the systems that guide scientific decisions.

The CSO will own Bio's scientific direction at the portfolio level - ensuring that promising ideas are rigorously evaluated, translated into testable programs, and moved into labs. The right person brings deep scientific credibility, experience with drug development, and the ability to attract and guide top-tier researchers.

A key requirement is meaningful exposure to the drug development and approval process - having observed programs through preclinical, IND-enabling, clinical, and regulatory stages.

What the CSO will actually do1. Own Bio’s portfolio-level scientific direction

Review projects launching on Bio Protocol, maintain a clear portfolio view of what's strongest and most promising, and make judgment calls on what to prioritize and what not to pursue.

2. Translate AI outputs into lab-validated science

Work closely with Bio's AI team to take AI-generated hypotheses and move them into experimental validation. Design and oversee the processes that turn computational insights into real, testable scientific results - quickly and rigorously.

3. Lead scientific diligence and evaluation

Build scalable processes to assess scientific credibility, risk, and potential across projects. Translate reviews into clear recommendations for go/no-go decisions and portfolio prioritization.

4. Recruit and support top-tier scientists

Develop and execute a strategy to bring world-class researchers into Bio's ecosystem - leveraging academic networks, conferences, and partnerships. Serve as a scientific sparring partner to researchers, helping refine hypotheses and stress-test approaches.

5. Represent Bio's scientific credibility externally

Act as Bio's scientific voice with academics, biotech operators, investors, and ecosystem partners. Stay current on scientific and biotech trends, and represent Bio at conferences and industry events.

6. Build an AI-native scientific operating model

Work with Bio's systems and knowledge infrastructure to develop AI-driven workflows for research review, synthesis, and evaluation - so scientific judgment scales with the platform.

7. Lead and grow the Science team

Hire, mentor, and manage Bio's Science team. Ensure the team operates at a high level and delivers on Bio's scientific mission.

The profile we’re looking for

A strong scientific foundation (PhD or equivalent depth) combined with experience outside of pure academia. This person should 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.

Experience that really matters
  • Senior scientific leadership, ideally with portfolio-level exposure (e.g., biotech fund, biotech company with multiple programs, or similar environment)

  • Demonstrated understanding of drug development realities, regulatory risk, and translational challenges

  • Track record of attracting, advising, or leading researchers and scientific teams

  • Comfort operating at a strategic level while staying close to the science

  • Interest in AI-native approaches to scientific work

Metrics & KPIs
  • Quality and progress of scientific assets under management

  • Speed and rigor of AI-to-lab translation pipeline

  • Caliber of researchers recruited into the Bio ecosystem

  • Scientific credibility and reputation among academic and biotech partners

  • IP generation and commercial viability of portfolio science

What success looks like after 12 months
  • Established a clear, credible scientific strategy at the portfolio level

  • Built a functioning pipeline from AI-generated hypotheses to lab validation

  • Recruited high-caliber scientists into Bio's ecosystem

  • Developed scalable diligence and evaluation systems informed by drug development experience

  • Strengthened Bio's scientific reputation with researchers, partners, and the broader biotech community

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