Designing for data-intensive and scientifically complex products means translating uncertainty into clarity: the process of making information usable, understandable, and trustworthy even when the underlying science or technology behind it is constantly changing. This session explores how UX practitioners can design for evolving domains like biotechnology, healthcare, and AI, where user needs are often unclear and priorities shift quickly. Drawing from real case studies in biomedical visualization and data platform design, attendees will learn practical ways to combine qualitative and quantitative research to guide design decisions and communicate evidence across teams. The session will share how to transform ambiguous requirements into clear, data-informed experiences that help users explore complex information with confidence. Attendees will leave with actionable strategies for designing clarity in complex systems, and methods to turn data and ambiguity into intuitive, transparent experiences that align users, technical teams, and stakeholders.