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UX Researcher - (Biotech)

ExecutivePlacements.com

Salary not specified
Nov 2, 2025
New York, NY, United States of America
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Prescient Design is seeking to develop AI and agentic frameworks to revolutionize drug discovery, and needs a UX Researcher to ensure the agentic framework is intuitive and seamlessly integrated into the complex workflows of cutting-edge drug discovery

Requirements

  • 3-5 years of experience conducting UX research and usability testing, preferably with complex, expert-facing systems or internal tools
  • 3-5 years of experience in qualitative and quantitative research methods, including generative and usability studies, data analysis, and A/B testing
  • Demonstrated experience with AI products, specifically Large Language Models (LLMs) and AI agents
  • Experience with UserTesting, Contentsquare, or similar usability testing platforms
  • Hands-on experience with LLM-based applications and standardized protocols like MCP (Model Context Protocol)
  • Experience working directly with subject matter experts and stakeholders on internal tools
  • Experience building and scaling a user research practice, including establishing processes for recruitment, testing, and knowledge management

Responsibilities

  • Define AI Product Strategy Through UX Research
  • Design and Execute Rigorous Usability Studies for AI Products
  • Operationalize User Feedback for AI Systems
  • Uncover Actionable Insights for Agentic Frameworks
  • Build a User-Testing Infrastructure for Internal AI Tools
  • Collaborate Deeply with AI/ML Engineers & Scientists
  • Communicate with Clarity and Impact

Other

  • 3-5 years of experience
  • Direct experience shipping internal software, tools, or products within biotech, pharma, or a related industry
  • Strong analytical skills and are comfortable synthesizing complex, often ambiguous, qualitative data into clear, actionable themes
  • Communicate with clarity, empathy, and a strategic focus
  • Enjoy tackling ambiguous, high-stakes problems and have a genuine curiosity for understanding complex domains like drug discovery