Bio

I am a fourth-year undergraduate and second-year master's student studying at the intersection of American political science and computer science, statistics, and data science. I have conducted research applying machine learning and statistical models on voting and election trends in the US at Stanford Engineering School, Tufts University's MGGG Redistricting Lab, political campaigns, PACs, nonprofits, and consulting firms. I aim to make our democracy fairer and more (racially, socioeconomically, politically, etc.) representative of the American public.

MS: Management Science & Engineering, concentration in computational social sciences
BA: Data Science & Social Systems, concentration in socio-political behavior analysis

Current Role at Stanford

Masters student in Management Science & Engineering. Undergraduate student in Data Science. Peer Advisor in Data Science. Resident Assistant.

Service, Volunteer and Community Work

  • Data Analyst, Stanford Data and Mapping for Society

    Pro bono data analysis for social and government sector organizations

    Location

    Stanford, CA

  • Policy Analyst, Cardinal Policy Group

    Pro bono policy analysis and research for social and government sector organizations

    Location

    Stanford, CA

Contact

  • Academic
    amhong@stanford.edu
    University - Student Department: Data Science Position: Undergraduate
    University - Student Department: Management Science and Engineering Position: Graduate

Additional Info

  • Mail Code: 6125

Links

Professional Interests

Looking for professional opportunities in progressive, Democratic, and nonpartisan political data analytics and engineering. I use data to understand social-political behavior and improve tech on the left. I do freelance political data journalism & consulting for campaigns, consulting firms, and newspapers. Inquiries: andmhong@gmail.com

I bring 5+ years of experience in political consulting, local/state & federal campaigns, research, nonprofits, coalitions, policy, lobbying, and activism. I was brought into this work as a grassroots organizer from redlined South Seattle.

LinkedIn: https://www.linkedin.com/in/andrew-hong-7364b4192/

Work Experience

  • Research Data Analyst, WA Community Alliance Data Hub (State Voices & America Votes VAN) (January 2023 - Present)

    Electoral data research for partnered organizations, PACs, and funders. StateVoices & AmericaVotes WA State Table VAN management. Building, learning, doing nerdy political things.

    Location

    Seattle, WA

  • Data Science Intern, Climate Cabinet Action (June 2023 - December 2023)

    - Built ML models to predict ticket-splitting and undervoting patterns to bolster political strategy, ROI
    - Updated geospatial ETL pipelines, Regex webscrapers to improve election data parsing for strategy analysis
    - Wrote analysis blogs to communicate technical insights to strategy for non-technical audiences
    - Engineered webscrapers, APIs to automate updating legislator database
    - Transformed wide-ranging geospatial data to analyze the relationship between partisanship and clean energy economic potential by district

    Location

    San Francisco, CA

  • Software & Analytics Researcher, MGGG Redistricting Lab, Tufts University

    - Co-built Python software package (VoteKit) to simulate social choice elections
    - Researched spanning trees methods to optimize generating randomized redistricting plans (GerryChain)
    - Contributed to novel applications of topological data analysis on elections
    - Built ideological spatial models for ranked-choice voting elections

    Location

    Medford, MA

  • Computational Research Assistant, Stanford University, School of Engineering (October 2022 - June 2023)

    Social choice and elections data analysis on ranked-choice voting among voters of color.

    Location

    Stanford, CA

  • Data Analyst, More Equitable Democracy (June 2022 - September 2022)

    Data analyses and development of multi-member district map proposals. Deep analysis on electoral system outcomes in local jurisdictions. Comms for ranked-choice voting ballot measure campaign (Portland, OR Measure 26-228–won by double digits).

    Location

    Seattle, WA

  • Associate Consultant, Prism West Political Consulting (March 2021 - September 2021)

    www.prismwashington.com | Helping elect a new bench of progressives across Washington. Fundraising database management, voter targeting algorithms (VAN), management consulting, comms/press, policy development, and data-backed campaign strategies. We won 15/16 of our 2021 primary races, unseating two incumbents.

    Location

    Seattle, WA

All Publications

  • Youth sociopolitical development: A conceptual framework by racial and gender minoritized youth organizers. American journal of community psychology Malorni, A., Dolan, S., Hong, A., Joseph, N., Mohamed, K., Moore, L., Phan, L., Skoglund, I., Too, I., Wittman, S. 2023

    Abstract

    Youth sociopolitical development (SPD) is a powerful protective and promotive factor for marginalized adolescents' social, emotional, physical, and academic well-being. Despite having unique insight and experiential knowledge about SPD processes, youth have been excluded from conceptual framework and model development. As part of a Youth Participatory Action Research project, 11 adolescents (ages 14-19) and one adult ask "How do adolescent community organizers with varying social and political experiences conceptualize youth SPD?" We used a multiple case study design, with a grounded theory analytic approach. The YPAR collective identified four interrelated, experiential domains of youth SPD: thinking, feeling, doing and relating. Within each domain, we identified and defined key constructs and practices. The YPAR collective's qualitative inquiry resulted in more nuance for existing frameworks of critical consciousness and critical action, and the collective pushes the SPD field to better integrate social and emotional aspects of SPD practice. They offer a conceptual framework that is rooted in their experiential, sensory, learned, and social knowledge, from a multiple-marginalized positionality. These insights enrich the fields of SPD research and practice.

    View details for DOI 10.1002/ajcp.12729

    View details for PubMedID 38151829