I built an interactive Pain-Point Chart app from AI-generated JSON and published a dashboard visualizing top customer frustrations.

I refined and finalized a customer journey map using AIDA, iterating on an AI-first draft and stakeholder feedback to produce a polished deliverable.

I designed and refined a consumer survey on high-fidelity wireless speakers, used AI to generate and improve questions, and built outreach and chatbot flows to collect responses.

I analyzed survey data from a 20-response Google Sheet and calculated percentages, means, medians, and modes for closed-ended questions to summarize consumer preferences for high-fidelity wireless speakers.

I sourced three Seed/Series A HR and recruiting AI startups and shortlisted one for deeper diligence.

I compiled a full company overview and funding history for HelloSky, synthesizing public records and announcements into a single diligence document.

I built a Week 1 holiday planning document and used SQL with an AI co-pilot to produce repeatable answers from Breaking Games' raw data.

I built a clean product dimension, joined scattered tables into a unified customer-journey view, and produced a holiday reorder recommendation based on aggregated product performance.

I built a Q4 ad allocation plan that tied Meta ad spend to revenue and recommended which campaigns to keep, cut, or grow.

I diagnosed Breaking Games' cart-abandonment data, removed bot-like sessions, and recalculated the true abandonment rate for a matched July range.

I chose and evaluated a public health dataset and committed to it as the basis for further analysis.

I mapped the County Health Rankings dataset and prepared it for analysis, documenting units, dimensions, and preprocessing steps.

I ran a Pearson correlation between county unemployment rate and uninsured rate and wrote a plain-language story of the findings.

I stress-tested my county-level correlation between unemployment and uninsured rates and documented limits, reasoning, and next steps.