Lifescience Scientist

What You’ll Do

Build PLG products on the Patsnap platform

Identify high-leverage use cases across clinical development, translational medicine, business development, competitive intelligence, and regulatory affairs.

Turn Patsnap’s deep data assets, including clinical trials, sequences, targets, deals, and patents, into MCPs, Skills, and Agents that solve real workflow pain points.

Launch quickly in “research preview” mode so users can try new capabilities within weeks, then continuously iterate based on feedback.

Translate customer needs into product direction

Spend meaningful time with researchers, scientists, BD teams, clinical operations teams, and other life sciences users.

Go beyond what users say they want and uncover what they are truly trying to accomplish.

Break down workflows until you can identify the “last 200 meters” where existing tools stop and users start struggling.

Decide what to build, what not to build, and where Patsnap has a unique right to win.

Design capabilities for different user groups

Understand how different users need different views of the same underlying data. For example, a clinical operations team and a BD leader may look at the same clinical trial but need completely different insights.

Design Skills and Agents that feel tailored to each workflow while maintaining consistency across the broader platform.

Use your industry judgment and understanding of PatSnap’s platform capabilities to make smart prioritization decisions.

Guide PM and marketing teams

Act as a domain authority for the life sciences product line.

Help PM teams develop a strong sense of what “good” looks like in this market.

Work closely with marketing to ensure positioning, content, and go-to-market strategy reflect the product’s real value, not just surface-level features.

Help the broader team build product taste, not just product requirements.

Required Qualifications

PhD in life sciences, bioinformatics, computational biology, or a related field, or equivalent deep industry experience in pharma, biotech, clinical development, translational medicine, BD, or competitive intelligence.

Genuine curiosity about how AI will reshape life sciences workflows, and a belief that Agents will change how work gets done in this industry.

A track record of delivering something end to end, such as a research paper, tool, internal product, data pipeline, or workflow solution.

Strong product intuition: when looking at an early prototype, you can quickly judge whether it is likely to work for real users.

Comfort working in uncertainty, moving quickly, and building products at the edge of current model capabilities.

Nice to Have

Hands-on experience with LLMs, Agent frameworks, MCP, or prompt engineering.

Experience working with structured biomedical data, such as clinical trial databases, sequence databases, target/disease ontologies, or deal and patent data.

Experience designing products for technical end users, including researchers, developers, data scientists, or scientific analysts.Open-source contributions, technical writing, public projects, or a visible portfolio of work.

What Makes This Role Different

You will not simply write requirements or manage a roadmap. You will help define what the next generation of life sciences AI products should feel like.

You will bring domain expertise, product judgment, and customer understanding together to build tools that are not just powerful, but genuinely useful in the daily work of scientists, analysts, and decision-makers.