Causal Foundry
Analytics Platform
Client
Causal Foundry
Year
2024
My Role
Lead Designer
Causal Foundry was launched with a grant from the Bill & Melinda Gates Foundation to improve healthcare outcomes in the Global South through personalized incentives. The initiative partnered with NGOs to integrate CF’s technology into their programs, using custom AI and ML models and data-driven tools to inform better health decisions at the individual level.
As Lead Designer, I shaped core product workflows, facilitated client workshops and usability testing, and established scalable design system foundations. I collaborated closely with data scientists, engineers, and researchers to deliver accessible, data-rich interfaces, while also building and managing the design team.
User research revealed that many end users had limited experience with analytics platforms and varied levels of data literacy. To support them, I designed clean, task-focused workflows for intervention creation, cohort segmentation, and outcome tracking, informed by biweekly research and demo sessions with partners.
A central focus was the data visualization system. I worked with engineers to design a flexible charting framework that scaled across use cases and data types. This included modular chart tiles with responsive layouts and interactions such as tooltips, filters, zoom, and legends, along with solutions for edge cases like missing or minimal data. This ensured clarity, consistency, and scalability across the platform.
As the product matured, I formalized design documentation in Notion, expanded the design system, and introduced structured processes for asynchronous collaboration. These foundations enabled faster iteration, stronger team autonomy, and more consistent user experiences as the platform scaled.
The redesigned platform delivered measurable impact across both users and internal teams. Faster delivery cycles for new analytics features were enabled by the scalable design system, while a consistent interface simplified demos and strengthened marketing efforts. Improved internal alignment reduced friction between teams and accelerated workflows.
For end users, reliable and clearly presented data built trust, reduced the learning curve, and supported faster, more confident decision-making. Together, these outcomes established a future-ready foundation for growth and ongoing innovation.
