Data analyst focused on data quality, reporting, and applied analytics across healthcare, research, and business contexts.
I’m a data analyst who transforms messy, multi-source data into clean, trustworthy dashboards and reports that drive business decisions. I specialize in building semantic data models, defining KPIs, and delivering insights that stakeholders can act on.
I’ve supported stakeholders with dashboards and recurring reporting across nonprofit programs and telecom combining SQL, Python, Excel, and Power BI . My strength is translating business questions into structured analyses and communicating findings clearly to both technical and non-technical stakeholders.
My academic foundation includes an MS in Analytics (Georgia Tech) and an MS in Biomedical Engineering (Illinois Tech), giving me experience with data quality standards, statistical rigor, and working effectively in high-accuracy environments.
Professional roles that shaped my analytics and engineering skill set.
CDC BRFSS analysis of 134,702 respondents to identify demographic, behavioral, medical, and economic predictors of type II diabetes risk. Includes data cleaning, LASSO feature selection, model comparison, and public health interpretation.
End to end churn analysis pipeline: exploratory data analysis on 2M+ telecom customer records, feature engineering, segmentation by demographics and usage behavior, and a predictive classification model. Delivered retention strategy recommendations backed by monthly trend dashboards.
Built an end to end NYC Airbnb pricing model (EDA → feature engineering → Random Forest vs Gradient Boosting). Added an experimentation module that simulates an A/B test (Control: current prices vs Treatment: model recommended prices) and estimates revenue lift with bootstrap p-values.
Compared 6 ML classifiers (KNN, Logistic Regression, SVM, Naive Bayes, Random Forest, Neural Network) on the UCI Heart Disease dataset. KNN achieved the best test accuracy at 90%. Includes full preprocessing, EDA, ROC analysis, and confusion matrices.
Simulated influenza spread in a 21 student classroom using 100K Monte Carlo iterations and a discrete SIR model. Validated simulation output against theoretical Binomial distributions. Compared SIR vs. simulation across multiple scenarios.
Built an interactive analytics dashboard surfacing key business KPIs: conversion rates, churn metrics, customer segments, and trend sparklines. Designed for executive level storytelling with drill down capability.
Analyzed 3M+ rows of historical stock data to build predictive insights and an interactive financial literacy interface. Increased financial understanding for 77.8% of novice investors in user testing.
Built an inventory and financial tracking system for a used car dealership. Streamlines customer interaction data collection and revenue reporting with a MySQL backed dashboard.
I’m open to data analyst roles (healthcare or business). If my portfolio resonates, feel free to reach out.
Send a Message