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Elizabeth Cozzolino


  • Skilled mixed methods researcher with five years of experience in quantitative and qualitative methods who has been recognized with more than $50,000 in grant funding
  • Effective verbal and written communicator who can translate complex findings to key stakeholders with and without technical expertise
  • Curious, self-motivated individual with a unique combination of technical skills, driven personality, and passion for using data to create innovative, research-based solutions to business, academic, and social problems

Technical Skills & Knowledge

  • Stata, Excel, Python (pandas, numpy) SQL, R, Max QDA, SAS
Technical Knowledge
  • Descriptive statistical analysis (hypothesis testing, ANOVA, t-tests), inferential and multivariate statistical analysis (linear and logistic regressions, event history analysis, multi-level models, machine learning), qualitative methods (in-depth interviews, field observation, focus groups, survey design)


Researcher | Population Research Center, The University of Texas at Austin | 2015-Present
  • Creative and inventive project management skills demonstrated by a research design that combined advanced statistical analyses in Stata (fixed effects models, logistic regression, event history analysis) with original qualitative data collection (ethnographic observation of 250 cases, 30 in-depth interviews) resulting in two peer-reviewed publications
  • Skilled communicator with experience presenting findings at twelve professional conferences, including three invited talks
  • Innovative mixed methods research design was awarded more than $50,000 in grant funding, including $35,000 from national competitions
Research Assistant | Population Research Center, The University of Texas at Austin | 2014-15
  • Excellent teamwork and collaboration skills demonstrated by working on a team of researchers to code, clean, manage, and merge nationally representative datasets federally funded research projects, resulting in three peer-reviewed publications
  • Technical expertise demonstrated through selecting appropriate statistical techniques and methods to analyze data, including regression modeling (two-stage propensity score weighted logistic regression, cross-lagged structural equation modeling, etc.)
  • Strong leadership skills and experience supervising, teaching, and managing junior co-authors
Research Specialist | Office of Family Initiatives, Texas Attorney General | 2013-14
  • Conducted evaluation of policy initiatives using quantitative (logistic regression analysis in SAS) and qualitative methods (interviews with program participants) resulting in government reports that influenced state-level policies and programs
  • Comfort with industry-scale data from coding and analyzing administrative records


  • 2018 (expected May). PhD, Sociology & Demography, The University of Texas at Austin
  • 2012. BA, Sociology & Political Science, Temple University. Summa cum laude, Phi Beta Kappa