What I do

Current

Earlybird Software, Data Scientist

Earlybird works with companies and organizations to solve their data engineering and analytics problems. From soup to nuts that can be everything from porting clients’ existing on premise data to the cloud to dashboarding to advanced custom analytics, and everything in between.

At the beginning of a project I’m typically involved in ETL from existing data stores and third-party sources. This usually means integrating with one or several APIs, but it has also meant scraping websites, and cleaning and deduping data stored in spreadsheets and text files. I’ve even gone so far as to build a parser to automate transforming Word doc bullet points into database tables.

Over the lifespan of a project, I figure things out about this data and the data we generate, and present these findings to stakeholders. Depending on the question, this has spanned the gamut from clustering customers to sussing out the network relationships between different business locations to training models with the aim of predicting people’s future behavior.

Open Source Software

Author, multicolor package, July 2018 (accepted to CRAN August 2018)

Author, postal package, June 2018 (accepted to CRAN July 2018)

Co-author, rOpenSci monkeylearn package, February 2018

Co-author, rOpenSci roomba package, May 2018

Co-author, cowsay package, June 2018

Co-author, rlangtip package, March 2019

Reviewer & contributor, rOpenSci oec package, June 2018, August 2018

Contributor, tradestatistics project, January 2019

Contributor, owmr package, October 2018

Contributor, rOpenSci rodev package, October 2018

Contributor, beepr package, May 2018

What I Use

  • R, for
    • Web scraping, API pipelining
    • Supervised machine learning, network analysis, cluster anlaysis
    • RMarkdown for reproducible presentations
  • git, GitHub, BitBucket
  • SQL (MySQL, Postgres)
  • drake for reproducible workflow management
  • Continuous integration on Travis and Appveyor
  • Unit testing with testthat, code coverage on Codecov
  • Containerized environments with Docker
  • AWS (EC2, RDS, S3) e.g., installing R and configuring RStudio server, working with the S3 API
  • Some Python, Shiny, Spark
  • The bare minimum of JavaScript, HTML, CSS :)

Past

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, tended to the lab webiste, and programmed online experiments run on Amazon Mechanical Turk.

Behavioral Biology Lab, University of Chicago, Research Fellow

I designed a behavioral economics experiment to separate baseline risk preference from irrational risk aversion. The approach subtly varied risk and expected values in a novel gambling game I wrote in Python. We also measured participants’ physiological levels of stress hormones to study the effect of stress on decision making under uncertainty.

Education

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

Talks, Articles, etc.

New York R Conference, Using the Twitter and Google APIs to Track Fires in NYC talk, New York, NY, May 2019

Chicago R Unconference, mentor on the rtip package along with Jim Hester and David Smith, Chicago, IL, March 2019

RLadies NYC, drake for Workflow Happiness in R” talk, source code, New York, NY, February 2019

“A package for tidying nested lists” article on developing roomba, June 2018

rOpenSci unconf, co-author of the roomba package, Seattle, WA, May 2018

Data Skeptic Beer-in-Hand Data Science article, February 2018

rstudio::conf 2018 Diversity Scholarship, San Diego, CA

“Sentiment analysis of Slack reviews using R” article, source code, July 2018

“Monkeying around with Code and Paying it Forward” article on contributing to monkeylearn, April 2018

Interview at Earlybird Software, December 2017

RLadies Chicago, “Oktoberfest Edition: Beer-in-Hand Data Science” talk, Microsoft Technology Center, October 2017

Chicago Women’s Ultimate Summit, “Women in Chicago Ultimate Data Analysis”, Chicago, IL, February 2017

Other Orgs

Volunteer, Statistics without Borders, 2019-present

Reviewer, DataKind, 2019-present

2018 class of NASA Datanauts, January 2018

Former Co-Organizer, RLadies Chicago, 2017-2018

Captain, UChicago Women’s Ultimate Frisbee Team, 2015