Senior Scientist, Computational Biology, Life Science Strategy

What you'll do

• Integrate genomic, transcriptomic, imaging, and clinical data to inform trial design, patient selection, treatment response, and disease biology.
• Develop and apply statistical methods, reusable software, and AI/LLM workflows for research analyses and predictive models.
• Lead projects, mentor junior scientists, and communicate scientific findings to internal and external stakeholders.

What they ask for

• PhD in a related field, or a master’s degree with 3+ years of relevant experience, plus 2+ additional years of relevant industry or postdoctoral experience.
• Proficiency in R and/or Python, machine learning, LLM-based coding assistants, agentic frameworks, software engineering practices, and SQL.
• Strong statistics and data analysis skills, including real-world clinical data; experience analyzing large-scale biological datasets.
• Demonstrated project leadership and mentorship; strong communication and collaboration skills.

Nice to have

• Practical experience configuring or adapting LLMs for scientific work; expertise in RWE, survival analysis, causal inference, network/systems biology, or multimodal integration.
• Peer-reviewed publications or conference presentations; understanding of the drug development lifecycle.

Pay

$100,000-$160,000 USD base salary (CHI); $115,000-$175,000 USD base salary (NYC/SF)

Tools

R, Python, SQL, Copilot, Cursor, LLMs, agentic frameworks

AI focus

Use LLMs and other AI tools to accelerate coding, discovery, documentation, and review; prototype agentic workflows with foundation models and LLMs for insights and predictive models.