Anthropic
Life Sciences Operator, Lead
San Francisco, CA
H1B sponsorship available$300k-$320kDetected 5 days ago
NLPLogisticsResearchCommunication
About the role
- This role is for an entrepreneurial operator with proven hands-on experience generating and translating therapeutic hypotheses in a biotech setting.
- Identify and prioritize the areas where AI can most meaningfully accelerate life sciences research
- Turn promising scientific ideas into concrete, well-scoped efforts and see them through with speed and ownership
Responsibilities
- Work hands-on with Claude and Claude Science to explore hypotheses, design and analyze research, and show what's newly possible
- Partner across research, product, and go-to-market to shape strategy and bring scientific work to life
Requirements
- MD/PhD not required
- Excellent scientific taste and entrepreneurial instinct - a track record of identifying and capitalizing on compelling opportunities before they are obvious
- Years of experience required will correlate with the internal job level requirements for the position
- Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
- Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Nice to have
- 7+ years of direct experience taking ideas from concept to results in a company setting
Compensation
- $300,000 - $320,000 USD
Benefits
- Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience
Company info
- Previously founded or joined as a founding team member of a biotechnology startup
Visa & Work Authorization
- However, we aren't able to successfully sponsor visas for every role and every candidate.
- But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
- We do sponsor visas!
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This listing is sourced directly from Anthropic's careers page and normalized into a canonical job model.