Pharmaceutical R&D Domain Expert

About this Role

What you'll do

• Data QA and reviews: Vet the quality of pharmaceutical knowledge work tasks and model outputs, spotting missing behaviors, thin reasoning, unsupported efficacy or safety claims, and answers that read well but would not survive scientific or regulatory scrutiny.
• Instruction specs and golden datasets: Write high-quality instruction specs, produce golden solutions to drug discovery and development problems, and define new tasks that reflect how the work is actually done in industry.
• Benchmarks and domain depth: Design challenging pharmaceutical tasks and evaluation sets, and help build domain-specific skills and tools together with the research team.
• Calibration: Work with client researchers and specialists in adjacent fields to keep standards consistent, translating tacit development judgment into explicit, teachable criteria.

What you need

• Education: PhD or PharmD in a pharmaceutically relevant discipline, for example medicinal or organic chemistry, pharmacology, molecular biology, pharmaceutical sciences, or toxicology. An MD with substantive drug development experience also qualifies.
• Experience: 4+ years of substantive pharmaceutical or biotechnology research and development experience, at a pharmaceutical company, a biotechnology company, a contract research organization, or a translational research institute. Purely academic research with no drug development exposure is a weaker fit.
• Domain depth: Genuine specialization in at least one stage of the pipeline, for example target identification and validation, medicinal chemistry and lead optimization, preclinical pharmacology and toxicology, translational and biomarker science, clinical development, or regulatory affairs and CMC.
• Seniority: Clear progression to a senior level, for example Senior Scientist, Principal Scientist, Director of Research, or a VP level R&D role, with real ownership of a discovery project or development program.
• Research record: Peer-reviewed publications, granted patents, or contributions to programs that reached the clinic. Strongly preferred.
• AI fluency: Hands-on working use of large language models in your professional work, and the judgment to tell a well-reasoned answer from a plausible-sounding wrong one.
• Availability: Able to commit reliably to 40 hours per week for an initial engagement of 6 months.
• Location: Living in the Bay Area, California, and able to work on-site with the client's team multiple days each week, when required. Candidates not currently based in the Bay Area must be willing to relocate there at their own cost. Relocation assistance is not provided.
• Excellent written communication, and the ability to give precise, well-structured written feedback.

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