Hello, It's Me
Kaitlyn Kirt
And I'm a
Designing data-driven solutions where human insight meets technological innovation to create meaningful and measurable impact.
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Designing data-driven solutions where human insight meets technological innovation to create meaningful and measurable impact.
Download Resume
Kaitlyn is a Statistics and Cognitive Science student at Rice University passionate about using data, design, and AI to drive innovation. She’s pursuing a career at the intersection of tech, business, and human-centered design, with a focus on human-computer interaction and strategic impact. Always eager to grow and collaborate, Kaitlyn seeks opportunities where curiosity and creativity fuel real-world solutions.
Read MoreI'm currently working as a Summer Associate at the HHX Innovation Hub at Howard Hughes Holdings, where I contribute to AI-driven initiatives that support innovative placemaking and real estate development. My role involves building machine learning models, evaluating startup technologies, and helping integrate emerging tech into real-world systems that shape how communities live, work, and connect.
Read MoreIn summer 2024, I worked as an IT Consulting Intern at Slalom in Houston, where I used AI and Power BI to deliver data-driven insights for an oil and gas client. By analyzing 10,000+ user feedback points, I created visualizations that informed key decisions for a new operational tool. I also honed skills in DAX and Power Query, engaged in leadership development, and supported proposal work and process improvements.
Read MoreIn March 2024, I completed a Quantitative Trading Externship at Belvedere Trading in Chicago, where I shadowed traders, researchers, and product managers to explore options strategies and real-time trade execution. I attended lectures on trading theory, observed live markets at the Chicago Board of Trade, and learned how Python is applied in project workflows and data modeling to drive trading efficiency.
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Conducting research on voting systems to evaluate user trust, credibility, and usability. Through human subject testing and survey tools like SUS, NASA-TLX, and TVS, the study compares electronic, optical scan, paper ballot, and lever machines to identify the most secure, trustworthy method for fair and reliable elections.
Analyzed how GDP and social conditions affect national happiness scores. Found GDP has a stronger impact on happiness in non-Western countries and low-social-condition regions. In Western countries, other factors like public health and social support seem more influential. Economic growth boosts happiness most when paired with strong social infrastructure.
Analyzed spatiotemporal trends in Los Angeles homicides using data from 2010–2024. Assessed impacts of unemployment, evictions, income, and police funding on crime. Found that homicide rates rose post-pandemic, especially in wealthier areas, and were influenced by geography more than enforcement. Models revealed that economic instability and housing insecurity are stronger predictors of crime than budget increases.
Analyzed over 10,000 GenAI chatbot interactions using Power BI dashboards developed during my internship. Tracked user sessions, question volume, answer clarity, and sentiment across 33 users and 113 sessions. Used Power Query and DAX to uncover engagement patterns, identify unclear responses, and highlight areas for improvement. Insights supported strategic enhancements to chatbot design and improved reporting efficiency.