Dallas, Texas, United States
Analytical and detail-driven data professional with several of experience transforming complex datasets into actionable insights across healthcare, behavioral health, and federal initiatives. Skilled in SQL, Python, R, and Power BI, with expertise in data quality, governance, and reporting automation. I design scalable data pipelines, modernize reporting systems, and collaborate cross-functionally to drive data-informed decisions. Passionate about bridging analytics and strategy, I’m expanding my impact into technology, financial services, and enterprise data environments - applying my strengths in data management, quality assurance, and agile teamwork to solve complex organizational challenges.
Analyze and manage large-scale federal health datasets using R, Python, SQL, and Power BI to support 988 Suicide & Crisis Lifeline and Zero Suicide program evaluations. Build automated data pipelines and dashboards to improve data quality, governance, and reporting efficiency across behavioral health initiatives. Translate complex data into actionable insights and visualizations that inform national policy, operational strategy, and stakeholder decision-making. Collaborate with cross-functional teams to modernize reporting systems, ensure data integrity, and deliver evidence-based recommendations for program performance improvement.
Designed and implemented machine learning models (Python, R) for geographic source attribution of Salmonella Enteritidis using whole genome sequencing (WGS) data from 300K+ isolates (2014–2022). Developed data pipelines, KPI dashboards, and automated Power BI reports to monitor partner engagement, outbreak response, and performance metrics across 200+ international sites. Provided technical consulting and data-driven insights for global partners, enhancing surveillance accuracy and operational efficiency across multiple capacity-building projects. Led creation of training modules and analytical frameworks for outbreak investigation, WGS data utilization, and public health surveillance. Translated insights from focus groups and stakeholders into actionable strategies to improve data quality, visualization, and partner engagement.
Conducted data wrangling, statistical analysis, and manuscript preparation for community-based epidemiological studies (500+ participants) examining risk factors for Staphylococcus aureus in low-resource settings. Partnered with microbiologists to perform molecular epidemiology and biostatistical analyses using R, producing figures and tables for peer-reviewed publications.
Supported large-scale COVID-19 surveillance and serological testing for ~3,000 participants in partnership with the City of Berkeley and University Health Services. Managed data collection and analysis across multiple cohorts and contributed to a peer-reviewed publication on qualitative study findings. Conducted contact tracing and case investigations as a certified California Department of Public Health Contact Tracer.