Masters in Epidemiology professional with a drive to provide expert advice, analyze complex data, and contribute to evidence-based research with an emphasis human health outcomes. Possesses diverse experience and knowledge in epidemiology, biostatistics, quantitative and qualitative data analysis, and rigorous statistical methodologies. Collaborative and dependable individual highly proficient in various statistical tools (SAS, STATA, R, Excel), providing analytic and programming support for prospective epidemiologic and clinical research studies, and disseminating key research findings effectively through strong leadership and communication skills.
GPA: 4.0
• Provide analytical support to a prospective research study performing multivariate Cox regression and linear mixed models; interpreting SAS outputs to assess public health issues and enhance research credibility
• Lead execution of analytical methodology and data management activities, becoming subject matter expertise on
research data by resolving data issues, managing analytic files, and writing SAS codes contributing to project success
• Contribute novelty to scientific community presenting study deliverables/results (data reports, presentations, and manuscript development) to diverse stakeholders
• Collaborate with Principal Investigator, actively supporting development and revisions of 2 study protocols. Applying epidemiological knowledge to draw analytical solutions for research objectives
• Developed appropriate statistical analysis plan for exploratory research questions extracting and analyzing relevant variables from clinical research data generating meaning insights for research team
• Leveraged STATA programming and quantitative analysis skills to perform 3 ordinal logistic regression models to support future clinical health disparities studies; creating tables, listings and figures to translate results
• Ensured integrity of analysis, handling clinical data in compliance with organizational data protection regulations, sharing agreements, and ethical considerations
• Reduced potential for bias, and produced timely deliverables, and enhanced data quality adhering to 2 Standard Operating Procedures, demonstrating scientific research methods and implementation knowledge
• Validated need for real-world data to drive analysis of novel infectious disease and vaccination coverage estimates collecting COVID-19 data from 3000+ cases, informing public health policy and guidelines
• Received cross-functional team recognition for data-driven strategies used, utilizing electronic health records (EHRs), electronic case reports (eCRs), and electronic laboratory reports (eLRs) to increase notification of potential exposures
• Identified data discrepancies and inconsistencies performing quality control checks of 1500 cases, proactively resolving issues to improve data quality for accurate analysis in Texas COVID-19 surveillance database
• Spearheaded 6 laboratory sections of 170+ students to build experimental research projects with data collection and statistical analysis plans; providing individualized support and feedback to improve analytical methodologies
• Enhanced student proficiency in statistical analysis, receiving 98% positive feedback on instruction effectiveness in teaching basic biostatistics and statistical programming using R and Excel to validate research results
• Enabled critical thinking and quantitative reasoning implementing lesson plans of 3 professors while managing 65+ projects’ timelines, resource needs, budget, and progress, showcasing task allocation ability
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