I turn complex data into dashboards people actually want to use.
Projects I've designed and built.
A full-featured barbershop management dashboard with appointment scheduling, client tracking, service pricing, wait time management, analytics, and payment processing.
A baby care tracking dashboard that visualizes feeding schedules, diaper changes, sleep patterns, and medication logs from Huckleberry CSV exports.
An interactive dashboard analyzing personal Amazon purchase history from 2020–2026, with spend trends, category breakdowns, monthly patterns, and top purchases visualized through Chart.js.
Academic work from my graduate studies in epidemiology and biostatistics.
A public health surveillance study analyzing 30,870 confirmed COVID-19 cases from the Chicago Department of Public Health in 2020. Using SAS Studio, the analysis examined demographic trends in emergency room utilization across age, sex, and race/ethnicity over a six-month period. Bivariate analysis with chi-square testing assessed crude associations, while multivariable logistic regression identified independent predictors of ER visitation, adjusting for clinical symptoms, comorbidity burden, and demographic factors.
A biostatistical analysis of 3,747 subjects from NHANES examining predictors of thyroid stimulating hormone (TSH) levels in the blood. Using SAS, the study applied univariate and multivariate linear regression with log transformations, variable selection via backward, stepwise, and Mallows' C(p) methods, and residual diagnostics to assess model fit. The final predictive model incorporated age, ethnicity, BMI, and blood metal concentrations (cadmium, barium, tungsten) as key predictors.
A cross-sectional epidemiological study using 2017–2018 NHANES data to assess the association between cholesterol levels and depression among 5,097 U.S. adults. The analysis employed univariate, bivariate, stratified, and multivariable logistic regression in SAS, with confounding and effect modification evaluated using Breslow-Day tests of homogeneity and Cochran-Mantel-Haenszel adjustment. Backward model selection was applied to identify the most parsimonious model, adjusting for demographics, lifestyle factors, comorbidities, and health conditions.
Where I've been and what I bring.
I lead data strategy and technology infrastructure across multiple skilled nursing facilities, aligning analytics with clinical, operational, and financial goals. My work focuses on improving CMS Star Ratings, rehospitalization rates, clinical outcomes, and patient satisfaction through cross-functional collaboration and data-driven performance initiatives. I also oversee data integrity, HIPAA compliance, cybersecurity standards, vendor partnerships, and staff training to strengthen data literacy and operational efficiency.
I served as Quality Control Project Lead across five clinical studies in immunology, oncology, and biotechnology. I was responsible for planning and executing QC on SDTM datasets, derived analysis databases, and the statistical outputs that informed regulatory submissions. I also developed programming documentation, worked closely with both internal teams and external clients to deliver technical solutions, and built and validated new macros and process tools that our team adopted across projects.
I programmed SDTMs, derived datasets, summary tables, listings, and figures for clinical trials. I built macros ranging from simple utilities to complex automation, and contributed to the review and refinement of dataset specifications and summary shells. This was a collaborative, fast-paced environment where I sharpened my SAS programming and clinical data skills.
I interviewed individuals with probable or confirmed COVID-19 infections at UIC, guiding them through isolation and quarantine protocols. I maintained ongoing contact to monitor symptoms and provide public health guidance, and handled data entry of all interviews and follow-ups in RedCap. This role deepened my understanding of epidemiology in practice and reinforced the importance of clear, empathetic communication in public health work.
I wore multiple hats during this internship — conducting contact tracing interviews, training other tracers on Salesforce, and supporting the Head Data Analyst with data management and Tableau dashboards. I also analyzed local COVID-19 trends against CDC risk factors and wrote a report on findings and policy implications. On the tech side, I served as the department's Salesforce advisor, handling troubleshooting, vendor communications, and software updates.
I worked alongside a Doctor of Chiropractic Medicine to develop and execute patient treatment plans, leading rehabilitation exercises and educating patients on health and wellness. Beyond clinical work, I helped run the clinic — managing scheduling, insurance checks, and administrative tasks — and played an active role in community marketing and planning monthly clinic events.
Master of Public Health
Epidemiology / Biostatistics
University of Illinois at Chicago (UIC), School of Public Health, May 2021
Bachelor of Science in Kinesiology
Movement Science
University of Illinois at Chicago (UIC), Dec 2016
Helen M. Barton Summer Undergraduate Research Scholarship
Feedback from colleagues and collaborators.
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