Computational Biologist

Responsibilities

• Improving the ability of LLM agents to execute long, coherent data-driven discovery tasks within real-world scientific environments and customer data infrastructures.
• Designing benchmarks to evaluate LLM agent performance, acceptance criteria, and failure modes on complex scientific tasks.
• Partnering directly with scientists and research leaders at client organizations to apply AI agents and make novel discoveries in biology.
• Serving as the scientific authority on AI-generated findings, evaluating the accuracy of discoveries for biological validity, identifying failure modes, and determining what warrants further investigation.
• Contributing to internal knowledge artifacts, scientific playbooks, and publications that advance the field of AI-driven biological discovery.
• Partner with GTM and account executives to scope engagements, define success metrics, and support pre-sales technical evaluation.
• Build trusted relationships with research scientists and research leaders with customers, earning credibility as both a scientific peer and a knowledgeable AI practitioner.

Requirements

• PhD in biological science, broadly defined; or equivalent demonstrated depth through professional experience.
• Familiarity with the regulatory and compliance landscape in pharma or biotech research.
• Experience analyzing one or more of the following types of complex biological data in a first-author publication: sc-omics data, high throughput screen data, proteomics or lipidomics data, human genetic data, imaging data, or protein structure data.
• Deep expertise in one area of mammalian biology and track record to rapidly develop working fluency in adjacent domains.
• Hands-on experience working with LLM and agentic AI tools in a biological research context.
• Strong critical thinking skills and ability to identify mistakes in LLM-generated analyses.
• Experience presenting scientific findings to both scientific and non-scientific audiences, across all levels, communicating biological complexity, AI limitations, and research outcomes.
• Bonus points for: Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep 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proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in Python and/or TypeScript/JavaScript with deep fundamentals, Strong proficiency in 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