About Me
I'm Mina Sonmez, a Cognitive Science and Data Science student at UC Berkeley passionate about understanding how people think, feel, and interact with technology. My work focuses on behavioral AI, UX research, and building data-informed digital experiences.
Whether it's exploring cognitive models, analyzing user behavior, or designing user-friendly interfaces, I enjoy turning insights into impactful, human-centered solutions. I thrive at the intersection of science, design, and innovation.
You can find me on LinkedIn to connect or follow my latest work:
Skills & Tools
Combining behavioral science and data to generate actionable product insights.
Behavioral Analytics (Amplitude)
Experienced in using Amplitude to analyze user journeys, cohorts, and product engagement trends.
Data Visualization (Tableau)
Skilled in turning complex datasets into clear, actionable dashboards for product and stakeholder decisions.
Survey Research (Qualtrics)
Designs and analyzes structured surveys to capture user sentiment, motivation, and behavior.
User Experience Tracking (Smartlook)
Interprets session replays and heatmaps to surface usability issues and user frustration points.
Lightweight Data Workflows (Airtable)
Uses Airtable for tagging research insights, organizing projects, and cross-functional collaboration.
Data Analysis (Python, SQL)
Applies Python and SQL to clean, analyze, and synthesize data, bridging quantitative depth with behavioral understanding.
Selected Projects
A few of my projects in behavioral data, research, and analytics
High School Integration App for Immigrants
A mobile/web application designed to support immigrant high school students in integrating into American education by offering tailored resources and mentor matching. Based on user input, the app curates educational resources, language support, and cultural integration materials.
World Population and Poverty Analysis
Analyzed global population and economic trends using Python and statistical methods to assess poverty and population growth factors. Processed and visualized large datasets to identify key social and economic patterns.
Climate Change — Temperatures & Precipitation
Analyzed a multi-decade climate dataset (210 US cities) to investigate temperature and precipitation trends. Implemented bootstrap confidence intervals and A/B hypothesis testing in Python to compare historical vs. modern climate data.