As Moober's Product Manager, I am scaling our ridesharing platform (1,350+ users) by leading a cross-functional team of six engineers, designers, and marketers using Agile and data-driven prioritization.

My role spanned strategy, product, and analytics—designing A/B tests, conducting user interviews, and using SQL insights to inform new feature rollouts, including commuter scheduling and real-time ride updates.

I supported a Web3 client by translating complex market and user research into an actionable strategy. I synthesized competitive analyses and user insights to identify high-value customer segments, directly shaping the client's go-to-market roadmap.

At Snap, I designed and developed AR filters in a cross-functional team using SnapML and JavaScript, creating interactive animal detection and live pet fashion styling experiences.

We deployed filters that received over 20,000 views in two weeks and improved engagement through iterative UX testing and rapid feedback loops.

I combined user research and data analytics to guide Spin's compliance and pricing strategies across 20K+ scooter ride data points. By conducting stakeholder interviews and surveys, I identified key policy and engagement trends.

I helped refine city partnership and pricing strategies by analyzing thousands of ride data points to pinpoint high-violation zones and optimize compliance.

At the Tagkopoulos Lab, I automated ontology mapping workflows using Pandas, fuzzy matching, and data preprocessing to fine-tune NLP models for biomedical text analysis. I built a preclinical studies database and enhanced dataset curation scripts for disease-drug prediction, with the goal to advance drug discovery and reduce R&D costs.

I defined product strategy and UX design for Liner's AI-powered study platform, driving an increase in feature adoption through data-driven decisions.

I led a team to build and iterate on Figma prototypes, introduced a guided onboarding experience, and used industry frameworks to prioritize roadmap items.