Experience

Adaptive Biotechnologies (Seattle, WA)

Data Analyst, November 2018 -

  • Financial planning and analysis, KPI development, and data management using Tableau, SQL, and R

Nevada State Democratic Party (Las Vegas, NV)

Deputy Data Director, August 2018 - November 2018

  • Used SQL and Data Studio to build dashboards and inform daily resource allocation and field operations for the top Democratic Senate campaign of 2018

  • Regularly performed predictive model assessment, geospatial analysis of voting targets, and other ad hoc analyses in R to inform big picture get-out-the-vote and voter protection strategies

National Endowment for Democracy (Washington, D.C.)

Stanford Fellow, July 2017 - September 2017

  • Wrote independent desk analysis of the NED’s grant making program in Burma
  • Reviewed grant materials and interviewed country experts to contextualize the NED’s role in the recent political transition and made recommendations for improved grant making practices in Burma and future transitions

Taoyuan City Government, Department of Education (Taoyuan, Taiwan)

Data analysis intern, June 2016 - August 2016

  • Used R for data cleaning, visualization, and basic statistical learning methods on data concerning high school and university outcomes in Taoyuan

Stanford University (Stanford, California)

Research assistant, January 2018 - May 2018

  • Literature review and survey design for Nathan Lee, PhD candidate in political science at Stanford University, in a study of local officials’ perceptions of policy expertise

Course assistant, June 2017 - March 2018

  • Helped design and organize EDUC 122Q / HISTORY 52Q: American Democracy in Crisis with Prof. Thomas Ehrlich

Bridge peer counselor, April 2017 - June 2018

  • Volunteered for weekly shifts to provide anonymous counseling for the Stanford community
  • QPR suicide protocol certified

Coursework

Stanford University

  • ENGR 150: Data Challenge Lab (Bill Behrman, Hadley Wickham)
  • STATS 116: Theory of Probability (Rachel Wang)
  • STATS 200: Statistical Inference (Joseph Romano)
  • STATS 204: Sampling (Rajarshi Mukherjee)
  • STATS 216: Statistical Learning (Robert Tibshirani)
  • POLISCI 150A: Data science for politics (Andrew Hall)
  • POLISCI 150B: Machine Learning for Social Scientists (Justin Grimmer)
  • POLISCI 150C: Causal Inference (Jens Hainmueller)
  • POLISCI 358: Data-driven politics (Adam Bonica)
  • HISTORY 4: Introduction to Geospatial Humanities (Zephyr Frank)

Other

  • OSPOXFRD 195Z: Tutorial in political science (Hongping Nie, Oxford University)
  • MTC 7186: Intensive Practical Chinese Reading & Writing (Murong He, National Taiwan Normal University)

Recent Posts

A draft of my recent work on leaked emails and political knowledge is now available for comment. Below is a copy of the abstract, for reference. In scholarly and popular discourse, leaks have long been associated with transparency, but their potential as a source of disinformation has gone largely unexamined. The turmoil of the 2016 U.S. presidential election cast doubt on leaks’ association with the truth by demonstrating the potentially disorienting impact of leaked emails on political knowledge and discourse.

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Before I enrolled in the Data Challenge Lab at Stanford, my approach to data science in R was almost entirely ad hoc. Beyond the very fundamentals of base R, I relied on a combination of Stack Overflow and code copied from textbooks and lecture slides to get anything done. Naturally, I couldn’t do much. The DCL changed all of that by introducing me to the Tidyverse, which not only gave me a unified set of tools to explore, visualize, and customize my data, but also gave me a much more intuitive sense for how data works and feels.

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While it’s hard to beat the ease and expressiveness of ggplot2 for most of my visualization needs, I haven’t always been terribly happy with how it’s default settings look. The process of creating a presentation quality plot usually involves toying around with the 80+ arguments of theme() and trying to remember what they control and what kind of element_ they are. It’s easy enough to remember how to change an axis.

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Some surprising news for those who spent the past year listening to me complain about writing my honors thesis: it’s time for round two! Thanks to the initiative and support of Professor Francis Fukuyama, I’ll be spending some time in the coming year revisiting the research I pursued as an honors student with the Center on Democracy, Development, and the Rule of Law. Funding comes courtesy of the Knight Foundation, and my findings will eventually be made available in a report written for Stanford’s Project on Democracy and the Internet.

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Welcome to my personal site. If you’re reading this, you’re probably a) my mother, or b) someone who’s interested in my background and experience as a data scientist. In either case, you’re in the right place! I plan to add content to this site in the form of either blog posts or project pages. Blog posts (like this one) will usually be quick and explanatory, and might include my thoughts on things I’m learning, tricky problems I’m facing, or maybe some bite-sized analyses.

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Projects

Scraping the news

Collecting and tidying headlines from Memeorandum.com

Policing trends in San Francisco

EDA of SF Police Department incident data

Four years on the farm

A quick analysis of my time at Stanford