Open to Summer 2027 internships

I turn messy data into clear stories.

Daniel Ho

Statistics & Data Science @ UT Austin
See my work Get in touch
metrobike_hourly.csv ŷ = 0.82x + 3.1 · R² = 0.91

Tools I work with

  • Python
  • R
  • SQL
  • pandas
  • scikit-learn
  • tidyverse
  • ggplot2
  • Jupyter
  • Git
  • Docker
  • Claude Code
  • Switch
projects shipped
4
datasets wrangled
12+
AI crew run from my phone
1

Selected work

Things I've built and questions I couldn't drop.

Featured · Hackathon, Nov 2026

Pocket Crew

A crew of AI agents I run from my phone through Switch. Claude builds, a different AI tests, and nothing ships until I say so.

  • Switch
  • Claude Code
  • OpenCode
  • GitHub Pages
View on GitHub
builder

Added dark mode. tester, please check it.

tester

Passes ✅ Toggle works and is remembered on reload.

Daniel

ship it ✅

builder

Shipped 🚀 live in ~1 min

Forecasting

Austin Bikeshare Demand

Regression on MetroBike trip data to forecast hourly rides by station from weather, time of day and class schedules.

  • Python
  • pandas
  • scikit-learn
View on GitHub

Dashboard

Longhorn GPA Explorer

Grade distributions by course and instructor in one interactive dashboard, so picking classes feels less like a coin flip.

  • R
  • Shiny
  • ggplot2
View on GitHub

Simulation

March Madness Bracket Model

Logistic-regression win probabilities fed into a 10,000-run Monte Carlo simulation of the whole bracket.

  • Python
  • NumPy
  • Logistic regression
View on GitHub

About

Stats student. Builder. Question asker.

I'm a first-year Statistics & Data Science student at UT Austin. I like taking a messy spreadsheet, asking it a sharp question, and coming back with a chart that actually answers it.

I work mostly in Python and R, and lately I've been building with AI agents, like a crew of them I run from my phone. Right now I'm learning statistical modeling: regression, resampling, and spotting when a model is lying to me.

How I work

  1. 01

    Ask a sharp question

    Pin down what decision the data should help with before touching it.

  2. 02

    Wrangle & model

    Clean, explore and fit the simplest model that holds up to checking.

  3. 03

    Ship a clear story

    One chart, one takeaway, and the code so anyone can rerun it.

  1. Nov 2026

    Flip the Switch Hackathon

    Built Pocket Crew solo in four days.

  2. 2026 – 2030

    B.S. Statistics & Data Science

    The University of Texas at Austin

Contact

Let's build something with data.

Internships, research, or a dataset you can't stop thinking about. My inbox is open.

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