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Elizabeth Cozzolino
Profile
- 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
Software/Programming
- 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)
Experience
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
Education
- 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