What I do
Earlybird Software, Data Scientist
What I do at Earlybird is twofold: at the beginning of a project I gather data and munge it into a form that we can use. This can mean integrating with an API, scraping websites, or cleaning and deduping data stored in spreadsheets. Then, we collect user data through our applications.
Over the lifespan of a project, I figure things out about this data and present these findings to stakeholders. Depending on the question, this has spanned the gamut from clustering users to sussing out the network relationships between different business locations, to training models that predict future customer behavior.
Experience and Cognition Lab, University of Chicago, Lab Manager
I ran traditional hypothesis tests and other statistical analyses on experimental data collected in the lab. I also contributed to the design of experiments and programmed online experiments.
Behavioral Biology Lab, University of Chicago, Research Fellow
I designed an experiment to separate baseline risk preference from irrational risk aversion by programming a gambling game to subtly vary risk and expected values. I also stressed a portion of participants and measured their physiological levels of stress hormones to study the effect of stress on decision making under uncertainty.
University of Chicago
Degree: Bachelor of Arts (2015) with general and departmental honors in Psychology; minor in French Literature. June 2015.
Honors: Lillian Gertrude Selz Prize for Academic Excellence (2012), Dean’s List (2011–’15), Phi Beta Kappa honors society (2014)
Honors Thesis, Behavioral Economics: An Exploration of Stress, Gender, and Risk Preference in Financial and Prosocial Domains
2018 class of NASA Datanauts, January 2018
Recipient of the 2018 rstudio::conf Diversity Scholarship, San Diego, CA, October 2017
RLadies Chicago, “Oktoberfest Edition: Beer-in-Hand Data Science,” Microsoft Technology Center, October 2017 Accompanying Interview at Earlybird Software, December 2017
Chicago Women’s Ultimate Summit, “Women in Chicago Ultimate Data Analysis,” Chicago, IL, February 2017
What I Use
- Steeped in the tidyverse, knitr, and Rmarkdown for reproducible presentations
- Web scraping, working with RESTful APIs
- Supervised and unsupervised machine learning, network analyses
- git, GitHub
- SQL (MySQL, Postgres)
- Competent in Python, Shiny
- Comfortable at the command line
usps package, June 2018
oec package, June 2018
monkeylearn package, February 2018
roomba package, May 2018
beepr package, May 2018
Former Co-Organizer, RLadies Chicago