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AI Scientific Business Analyst
Location: Remote / Foster City, CA
Experience: 10+ Years
Job Type: Full-Time
Role Summary
We are seeking an AI Scientific Business Analyst with strong Life Sciences and AI/ML knowledge to bridge business, scientific, product, data, and AI engineering teams. The ideal candidate will understand clinical research and drug development and be able to translate scientific/business needs into clear requirements for AI-powered solutions.
Required Qualifications
Bachelor's or Master's degree in Life Sciences, Health Sciences, Pharmacy, Biotechnology, Biomedical Sciences, or related field.
10+ years of overall experience, including 8+ years within Pharmaceutical R&D / Life Sciences.
Strong experience in Business Analysis, requirements gathering, and stakeholder management.
Experience supporting Clinical Research, Clinical Development, Translational Science, Oncology, or related therapeutic areas.
Strong understanding of the clinical development and pharmaceutical R&D lifecycle.
Ability to translate ambiguous business/scientific problems into structured functional and AI requirements.
Experience defining KPIs, success criteria, and measurable business outcomes.
Experience with UAT planning and execution, including test scenarios, defect tracking, retesting, and UAT reporting.
Strong communication, analytical, problem-solving, and stakeholder management skills.
Key Responsibilities
Partner with Product Managers, Business Leads, AI Leads, and Data teams to define AI use cases, requirements, success criteria, and outcomes.
Translate business/scientific needs into AI-ready requirements, including data inputs, model outputs, workflows, prompts, and dashboards.
Create and maintain user stories, acceptance criteria, URS/FRS, process flows, and data-flow documentation.
Define current-state/future-state processes and support requirements prioritization and solution feasibility.
Partner with AI/Data teams to define data specifications, source-to-target mappings, and AI input/output requirements.
Lead UAT planning and execution, including test cases, defect tracking, retesting, and UAT summary reports.
Track and communicate project status, risks, issues, dependencies, decisions, and assumptions.
Act as the bridge between scientific/business stakeholders and AI/technical teams to ensure alignment and successful delivery.
Preferred / Good-to-Have Skills
Understanding of AI/ML and Generative AI concepts.
Experience with AI products, analytics, intelligent automation, LLMs, AI agents, or prompt engineering.
Experience working in Agile/Scrum environments.
GxP / CSV knowledge.
Basic SQL for data validation and analysis.
Basic Python for exploratory data analysis.
Experience with Jira or Azure DevOps.
Work arrangement
Yes
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