Sean Bock

Sean Bock

PhD Candidate in Sociology

Harvard University


I am a Ph.D. Candidate and Researcher at Harvard University, where I am also an affiliate of the Institute for Quantitative Social Sciences (IQSS) and the Harvard Center for Population and Development Studies. I have 8 years of experience working on data-intensive projects—both alone and as a part of teams—performing every aspect of the data analysis process, including: collecting, cleaning, and managing data, performing statistical analyses, creating clear narratives with intuitive visualizations, and communicating insights through peer-reviewed publications and presentations at national conferences. I love finding creative ways to leverage data and building tools to help facilitate research workflows.

My academic research relies on large-scale surveys and text data to draw insights about politics, culture, and social change in the United States and Western Europe. My work has appeared in several top peer-reviewed journals and has been covered by news outlets, such as the New York Times, New Yorker, and Washington Post.

Download my resumé or Academic CV

  • Quantitative Research
  • Text Analysis
  • Survey Research
  • Data Visualization
  • PhD in Sociology, 2023

    Harvard University

  • AM in Sociology, 2020

    Harvard University

  • BA in Sociology and Political Science, 2016

    Indiana University, Bloomington


Data Analysis
Data Visualization
Text Analysis
Machine Learning


PhD Researcher
Harvard University
Sep 2017 – Present Cambridge, MA

Responsibilities include:

  • Designed, managed, and executed all aspects of 5 large-scale research projects using R and Stata
  • Analyzed large longitudinal and cross-national surveys using advanced statistical techniques, including multivariate regressions, cluster analysis, machine learning, and natural language processing
  • Communicated insights to different audiences in 6 first- and co-authored publications in top peer-reviewed journals, a non-technical article published in the Washington Post, presentations at national conferences, and interviews at media outlets
Research/Data Science Consultant
Washington University in St. Louis
Jun 2022 – Present Remote

Responsibilities include:

  • Consulted clients on research and data analysis strategies
  • Constructed tailored R package to improve research workstreams
Research Assistant
Harvard University
Aug 2017 – Jun 2021 Cambridge, MA

Responsibilities include:

  • Led team of research assistants on data cleaning, analysis, synthesis, and organization tasks
  • Extracted insights from survey and text data using unsupervised machine learning, regression, GLM, factor analysis, and other statistical techniques using R, Stata, and Latent Gold
  • Constructed intuitive data visualizations to convert research and data analysis into clear narratives
  • Managed large collaborative projects using version control (Git) and automated reporting with R Markdown
Teaching Assistant
New York University
Jan 2022 – Dec 2022 New York, NY

Responsibilities include:

  • Assisted in teaching over 30 NYU graduate students on text mining (natural language processing) methods using R
  • Developed and conducted weekly 1-hour coding demos on topics including: Machine learning, topic modeling, networks, web scraping, and visualization machine learning, regression, and decomposition techniques
  • Led weekly lab meetings and consulted students on coding assignments and research projects


Data science | Data Analytics

Golf Match Simulator App
An R Shiny app to predict outcomes in golf matches
kmodesFlow package
An R package to improve workflow with k-modes modeling. I demo package functionality by identifying latent customer groups of a telecom company, which are then used to predict customer churn.
Political Speech N-gram Viewer
An R Shiny app to search trends in words used in U.S. Presidential campaign speeches from 1954 to 2020
The Prevalence of Exclusionary Nationalism across Party Manifestos, 1920-2020
Using data from the Comparative Manifesto Project, I analyze trends in the prevalence of exclusionary nationalism present in party platforms. Results are shown with an interactive plot and heat map table.
Using sentiment analysis to identify the scariest season of Stranger Things
I analyze scripts from the popular show, Stranger Things, and use sentiment analysis to identify the scariest season. (Featured in Blog post).