Resume

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Education

B.A. in Public Policy, University of North Carolina at Chapel Hill, 2019
  • With Honors and Highest Distinction
  • Phi Beta Kappa
  • Minors in Philosophy, Politics, & Economics and Social & Economic Justice
  • MacDonald Community Service Fellow
  • Buckley Public Service Scholar
(HS) North Carolina School of Science and Mathematics
UNC Public Policy Logo Blue
Phi Beta Kappa Logo
CCPS Logo

Education

UNC Public Policy Logo BlueB.A. in Public Policy, University of North Carolina at Chapel Hill, 2019
Phi Beta Kappa / Honors and Highest DistinctionPhi Beta Kappa Logo
CCPS LogoMacDonald Community Service Fellow / Buckley Public Service Scholar
HS: North Carolina School of Science and MathematicsNCSSM Logo

Work Experience

Finance and Compliance Associate, NC Democratic Party
NCDP Logo
  • May 2017 - December 2018
  • First-ever salaried employee while still an undergraduate (Summer '18)
  • Data and Research: built targeted fundraising lists using vendor and NCDP scores; used the voter file (Votebuilder), NGP, BSD, and ActBlue for record-keeping; used Excel and WhoopDeDupe (VF-matching program) to manipulate data between databases and online sources
  • Other Duties: managed expenditures and receipts, regularly assisted in both federal and state campaign finance report reconciliation, wrote and consulted on external communications, planned party events, designed branded documents, event logos, social media graphics
  • Management: interviewed, taught, and supervised two interns each semester and summer

Research Experience

Honors Thesis, UNC-CH Department of Public Policy - August 2018 - April 2019
News-Related Social Media Use, Political Knowledge, and Participation in the 2016 Election
  • Data: 2016 CCES Common Content (survey data, unweighted n = 64,600)
  • Program Used: Stata (svy*, factor/rotate, margins, eststo/esttab, coefplot), R (ggplots, mapping)
  • Methods: exploratory factor analysis, logit & fractional logit regressions, margins
Term Project, UNC-CH Graduate School of Information & Library Science 625 - Spring 2019
Using Machine Learning Techniques to Predict the Fates of Bills from the 112th - 115th Congresses
  • Data: floor speech content, roll-call vote histories, district-level Census data from AFF
  • Programs and Packages/Nodes Used: Python, R, KNIME
  • Methods: web scraping, text processing incl. regular expresssions, API requests, k-Means cluster analysis, RandomForest decision trees, Naïve Bayesian modeling, logit regression
Research Assistant, UNC-CH Department of Sociology
  • Lab/Project: "Protest in 45's First 100 Days"
  • Spring 2017
  • Duties: news story research, sorting, and coding into database

Skills

Statistics Programs: Stata, R

Data Mining Programs: KNIME, Weka

Programming Languages: Python, HTML

Typesetting Languages: LaTeX, Markdown

Adobe Products: Illustrator, Photoshop

Statistics Programs: Stata, RData Mining Programs: KNIME, Weka
Programming Languages: Python, HTMLTypesetting Languages: LaTeX, Markdown
Adobe Products: Illustrator, PhotoshopExcel: PivotTables, VLookup & Index/Match, Mail-Merging
Languages: German - CEFRL B2 "Upper Intermediate," listen to native 6 o'clock news, daily
Spanish - took from 2nd through 11th grades, can still understand most written text
Basic American Sign Language