Data & Analysis
I enjoy working with numbers — cleaning up messy data, finding the trend that actually matters, and putting it in a way that's easy for everyone to act on.
Bangkok, Thailand · Open to opportunities
Business · Data · Operations
Final-year International Business student with a Computer Science background, based in Bangkok. I like digging into data and messy problems, and helping a team work out the smart next move.
I'm someone who sits comfortably between business and tech. My International Business degree taught me how markets, operations, and people work; my Computer Science and Embedded Systems background taught me to think in systems, break problems down, and let the data do the talking.
I like taking something messy — a spreadsheet, a workflow, a guest complaint — and figuring out what's really going on underneath. Whether I'm handling VIP guest lists or helping out with HR, my approach is the same: get it organized, ask a few honest questions, and make the next step clear for everyone. I'd rather take the time to understand a problem properly than rush to an answer that only looks neat.
I moved to Bangkok from Myanmar four years ago and built my studies and life here pretty much from scratch. That taught me more about adapting, staying calm, and reading a room than any class could — and it's a big part of why I work well with people from all kinds of backgrounds.
I enjoy working with numbers — cleaning up messy data, finding the trend that actually matters, and putting it in a way that's easy for everyone to act on.
I pay attention to how work really gets done day to day, so I can spot where things slow down or slip through — and suggest a simple fix.
My CS background means tech doesn't scare me. I can talk to developers, get the constraints, and help explain things clearly to the business side.
Growing up between cultures and working in hospitality and HR taught me to really listen — to what people mean, not just what they say — and to help a team stay on the same page.
A few things I've worked on, laid out simply — the problem, what I looked into, and what I recommended.
[VIP arrivals were flagged in a few different places, so guests occasionally reached the desk without being recognized.]
[Traced how a VIP flag travelled from booking → front office → housekeeping across ~2 weeks of arrivals, and where it got dropped.]
[One shared pre-arrival checklist, owned by the morning shift, checked at handover.]
[Add a real number or a manager's words — missed-VIP incidents before vs. after, or the feedback you got.]
[Candidates waited days between steps, and some strong ones dropped out before we replied.]
[Mapped the time between each stage for the last N candidates to find the slowest handoff.]
[A simple shared tracker plus a 48-hour "always reply" rule.]
[Add a number — average response time before/after, or the drop-off rate you cut.]
[The question the assignment (or a real situation) asked you to answer.]
[Your sources — market size, competitor pricing, demographics — and how you weighed them.]
[The call you made, and the one number or insight that decided it.]
[The grade, what the analysis concluded, or what you'd track to prove it right.]
Organization — Bangkok, Thailand
Sofitel Bangkok Sukhumvit — Bangkok, Thailand
Rangsit University — Thailand
University of Information Technology — Myanmar
Open to roles across business, operations, and data — internships or full-time. I'm still exploring where I fit best, so if you think there's a match, I'd love to hear from you. Email's the fastest way to reach me.