As a data-drive Venture Builder, Stryber had a proprietary process for identifying new business opportunities based on market trends and investment data. Leveraging the data points from various startup databases such as Pitchbook, Crunchbase, and YCombinator, however was manual, complicated, time consuming, and not scalable. I was tasked with creating a unified internal tool that would automate, enhance, scale, and democratize our research process across the organization.

As the primary designer and product manager, I worked alongside 3 engineers to create the first version of what would become Stryber Analytics, which leveraged our existing process but standardized and optimized it, as each individual had their own unique way of filtering and searching for promising startup ideas. Over the next few years, I worked with a data scientist to supercharge our ranking and filtering process and expanded adoption further across the organization.