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A small world network

Contact

Skills

Programming:
R, Python, SQL, Stan

Data science:

CSS workshops organized:

Disclaimer

This resume was made with the R package pagedown.

Last updated on 2023-01-04.

Main

Connor Gilroy

Computational social scientist & PhD candidate

Sociologist seeking roles in data science or quantitative social science. I have 7+ years of experience analyzing text, spatial, network, and survey data, with broad skills in statistics, programming, and written and visual communication of analytic insights. My dissertation research uses NLP methods and survey data to explain variations in expressions and experiences of community across digital and location-based contexts.

Employment

University of Washington

N/A

Seattle, WA

present - 2015

Graduate Teaching Assistant & Instructor: Taught sections and courses including sociological theory, data and society (undergraduate); social statistics, data science and population processes, Bayesian statistics for the social sciences (graduate); digital demography and word embeddings for social sciences (workshops)

Graduate Research Assistant: Analyzed Twitter networks of US homeless care organizations; built a web crawler and a PostgreSQL database to collect and store text data from nonprofit and government webpages (with Zack Almquist). Built an agent-based network model of public opinion change (with Katherine Stovel)

Meta

N/A

Seattle, WA

summer 2022, 2021, 2020

Data Science Intern (2022): Analyzed feed engagement with reshared Facebook Groups content, presented insights to the Director of Data Science for Communities, built a data pipeline to create a new metric, reanalyzed a collection of experiments to quantify tradeoffs between types of content, and launched a new experiment to assess incremental value of reshared content (Communities Ecosystem team)

Quantitative User Experience Research Intern (2020, 2021): Designed and conducted two studies (log data analysis with random forest models, behaviorally-targeted followup survey) of factors driving initial participation in new online communities (2020, Community Creation team). Designed, fielded, and analyzed a complex stratified survey of job seeker needs and satisfaction; wrote a widely-referenced technical guide to creating inverse probability weights for nonresponse using an internal Python tool; evaluated quality of an external vendor’s missing data imputation for a sensitive survey question (2021, Commerce Ecosystem team)

The World Bank Group

N/A

Washington, DC

2020

Consultant, Survey Data Analysis: Created statistical models and data visualizations of gender-based disparities in Central Asia; wrote reproducible R pipeline for updating reports with new waves of survey data

Epic Systems Corporation

N/A

Verona, WI

2015 - 2013

Quality Assurance: Automated and manual software testing for web APIs and enterprise healthcare software

Education

PhD, Sociology

University of Washington

Seattle, WA

expected 2023

Dissertation: “Expressions of Community: Understanding Variations in Community through LGBTQ Experiences.”

MA, Sociology

University of Washington

Seattle, WA

2018

Thesis: “How Distinct is Gay Neighborhood Change? Patterns and Variation in Gayborhood Trajectories.” Distinguished Thesis Award in Social Sciences, 2019. Joined webscraped and geocoded gay bar data with Census data to statistically compare trajectories of change in gayborhoods to matched neighborhoods.

BA, Biology and Geophysical Sciences

University of Chicago

Chicago, IL

2013

Selected Publications

Digital Traces of Sexualities: Understanding the Salience of Sexual Identity through Disclosure on Social Media

Gilroy, Connor and Ridhi Kashyap. Socius 7: 1–18. doi: 10.1177/23780231211029499

N/A

2021

Compiled a dataset through the Facebook Marketing API, fit Bayesian loglinear models to the results, and used simulations from those models to produce visualizations of variations in sexual identity disclosure rates by age, gender, and relationship status. Funded by an NIH Big Data to Knowledge (BD2K) fellowship.

Humans in the Loop: Incorporating Expert and Crowdsourced Knowledge for Predictions using Social Survey Data

Filippova, Anna, Connor Gilroy, Ridhi Kashyap, Antje Kirchner, Allison C. Morgan, Kivan Polimis, Adaner Usmani, and Tong Wang. Socius 5: 1–15. doi: 10.1177/2378023118820157. (corresponding author)

N/A

2019

Fit regularized regression models to predict life outcomes from survey data, varying the coefficient penalties according to human-derived variable importance ranking from a wikisurvey. Managed the reproducibility of our code base and coordinated the project writeup. Funded by the Russell Sage Foundation Summer Institute in Computational Social Science.